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Transformers for Natural Language Processing Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4【電子書籍】[ Denis Rothman ] 楽天Kobo電子書籍ストア	＜p＞＜b＞OpenAI's GPT-3, ChatGPT, GPT-4 and Hugging Face transformers for language tasks in one book. Get a taste of the future of transformers, including computer vision tasks and code writing and assistance. Purchase of the print or Kindle book includes a free eBook in PDF format＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Improve your productivity with OpenAI’s ChatGPT and GPT-4 from prompt engineering to creating and analyzing machine learning models＜/li＞＜li＞Pretrain a BERT-based model from scratch using Hugging Face＜/li＞＜li＞Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your data＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs? Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses. You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model. If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides. The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details). You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using DALL-E 2, ChatGPT, and GPT-4. By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Discover new techniques to investigate complex language problems＜/li＞＜li＞Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers＜/li＞＜li＞Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3＜/li＞＜li＞Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E＜/li＞＜li＞Learn the mechanics of advanced prompt engineering for ChatGPT and GPT-4＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞If you want to learn about and apply transformers to your natural language (and image) data, this book is for you. You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community to help guide you on your transformers journey!＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	7,748円
【中古】 Disney FAN (ディズニーファン) 2022年 07月号 [雑誌] / 講談社 [雑誌]【メール便送料無料】【最短翌日配達対応】古本買取本舗　楽天市場店	出版社：講談社JANコード：4910165830724■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　出荷まで48時間かかる場合があります。あらかじめご了承ください。■メール便は、1冊から送料無料です。※宅配便の場合、2,500円以上送料無料です。※最短翌日配達ご希望の方は、宅配便をご選択下さい。※「代引き」ご希望の方は宅配便をご選択下さい。■中古品ではございますが、良好なコンディションです。決済は、クレジットカード、代引き等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	376円
統計的機械学習の数理100問with　Python　鈴木讓/著ドラマ×プリンセスカフェ	■ISBN:9784320125070★日時指定・銀行振込をお受けできない商品になりますタイトル統計的機械学習の数理100問with　Python　鈴木讓/著ふりがなとうけいてききかいがくしゆうのすうりひやくもんういずぱいそんとうけいてき/きかい/がくしゆう/の/すうり/100もん/WITH/PYTHONきかいがくしゆうのすうりひやくもんしり−ず2きかい/がくしゆう/の/すうり/100も発売日202004出版社共立出版ISBN9784320125070大きさ251P　26cm著者名鈴木讓/著	3,300円
Time Series Analysis with Python Cookbook Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation【電子書籍】[ Tarek A. Atwan ] 楽天Kobo電子書籍ストア	＜p＞Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features ? Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms ? Learn different techniques for evaluating, diagnosing, and optimizing your models ? Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book Description Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting. This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you'll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you'll work with ML and DL models using TensorFlow and PyTorch. Finally, you'll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book. What you will learn ? Understand what makes time series data different from other data ? Apply various imputation and interpolation strategies for missing data ? Implement different models for univariate and multivariate time series ? Use different deep learning libraries such as TensorFlow, Keras, and PyTorch ? Plot interactive time series visualizations using hvPlot ? Explore state-space models and the unobserved components model (UCM) ? Detect anomalies using statistical and machine learning methods ? Forecast complex time series with multiple seasonal patterns Who this book is for This book is for data analysts, business analysts, data scientists, data engineers, or Python developers who want practical Python recipes for time series analysis and forecasting techniques. Fundamental knowledge of Python programming is required. Although having a basic math and statistics background will be beneficial, it is not necessary. Prior experience working with time series data to solve business problems will also help you to better utilize and apply the different recipes in this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	6,026円
Machine Learning for Time Series Forecasting with Python【電子書籍】[ Francesca Lazzeri ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Learn how to apply the principles of machine learning to＜/strong＞＜strong＞time series modeling with this indispensable resource＜/strong＞＜/p＞＜p＞＜em＞Machine Learning for Time Series Forecasting with Python＜/em＞ is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling.＜/p＞＜p＞Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting.＜/p＞＜p＞Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to:＜/p＞＜ul＞＜li＞Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality＜/li＞＜li＞Prepare time series data for modeling＜/li＞＜li＞Evaluate time series forecasting models’ performance and accuracy＜/li＞＜li＞Understand when to use neural networks instead of traditional time series models in time series forecasting＜/li＞＜/ul＞＜p＞＜em＞Machine Learning for Time Series Forecasting with Python＜/em＞ is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts.＜/p＞＜p＞Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,706円
Beginner's Guide to Streamlit with Python Build Web-Based Data and Machine Learning Applications【電子書籍】[ Sujay Raghavendra ] 楽天Kobo電子書籍ストア	＜p＞This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you’ll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models.＜/p＞＜p＞＜em＞Beginner's Guide to Streamlit with Python＜/em＞ begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You’ll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you’ll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit.＜/p＞＜p＞After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own.＜/p＞＜p＞＜strong＞What You Will Learn＜/strong＞＜/p＞＜ul＞＜li＞How to start developing web applications using Streamlit＜/li＞＜li＞What are Streamlit's components＜/li＞＜li＞Media elements in Streamlit＜/li＞＜li＞How to visualize data using various interactive and dynamic Python libraries＜/li＞＜li＞How to implement models in Streamlit web applications＜/li＞＜/ul＞＜p＞＜strong＞Who This Book Is For＜/strong＞＜/p＞＜p＞Professionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,469円
Bioinformatics with Python Cookbook Use modern Python libraries and applications to solve real-world computational biology problems【電子書籍】[ Tiago Antao ] 楽天Kobo電子書籍ストア	＜p＞Discover modern, next-generation sequencing libraries from the powerful Python ecosystem to perform cutting-edge research and analyze large amounts of biological data Key Features ? Perform complex bioinformatics analysis using the most essential Python libraries and applications ? Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and much more ? Explore various statistical and machine learning techniques for bioinformatics data analysis Book Description Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python. This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you'll explore the application of machine learning algorithms in bioinformatics. By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale. What you will learn ? Become well-versed with data processing libraries such as NumPy, pandas, arrow, and zarr in the context of bioinformatic analysis ? Interact with genomic databases ? Solve real-world problems in the fields of population genetics, phylogenetics, and proteomics ? Build bioinformatics pipelines using a Galaxy server and Snakemake ? Work with functools and itertools for functional programming ? Perform parallel processing with Dask on biological data ? Explore principal component analysis (PCA) techniques with scikit-learn Who this book is for This book is for bioinformatics analysts, data scientists, computational biologists, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems. Working knowledge of the Python programming language is expected. Basic knowledge of biology will also be helpful.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	6,600円
Financial Theory with Python A Gentle Introduction【電子書籍】[ Yves Hilpisch ] 楽天Kobo電子書籍ストア	＜p＞Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance.＜/p＞＜p＞Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of ＜em＞Python for Finance＜/em＞, Yves Hilpisch, ＜em＞Financial Theory with Python＜/em＞ explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other.＜/p＞＜ul＞＜li＞Draw upon mathematics to learn the foundations of financial theory and Python programming＜/li＞＜li＞Learn about financial theory, financial data modeling, and the use of Python for computational finance＜/li＞＜li＞Leverage simple economic models to better understand basic notions of finance and Python programming concepts＜/li＞＜li＞Use both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocation＜/li＞＜li＞Learn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy＜/li＞＜/ul＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,890円
Hands-On Data Structures and Algorithms with Python Store, manipulate, and access data effectively and boost the performance of your applications, 3rd Edition【電子書籍】[ Dr. Basant Agarwal ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Understand how implementing different data structures and algorithms intelligently can make your Python code and applications more maintainable and efficient＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Explore functional and reactive implementations of traditional and advanced data structures＜/li＞＜li＞Apply a diverse range of algorithms in your Python code＜/li＞＜li＞Implement the skills you have learned to maximize the performance of your applications＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.＜/p＞＜p＞By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Understand common data structures and algorithms using examples, diagrams, and exercises＜/li＞＜li＞Explore how more complex structures, such as priority queues and heaps, can benefit your code＜/li＞＜li＞Implement searching, sorting, and selection algorithms on number and string sequences＜/li＞＜li＞Become confident with key string-matching algorithms＜/li＞＜li＞Understand algorithmic paradigms and apply dynamic programming techniques＜/li＞＜li＞Use asymptotic notation to analyze algorithm performance with regard to time and space complexities＜/li＞＜li＞Write powerful, robust code using the latest features of Python＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,739円
【中古】フォローアップドリル化学物質の状態 / 数研出版株式会社 / 数研出版 [単行本]【メール便送料無料】【最短翌日配達対応】もったいない本舗　楽天市場店	著者：数研出版株式会社出版社：数研出版サイズ：単行本ISBN-10：4410275763ISBN-13：9784410275760■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　発送まで48時間かかる場合があります。あらかじめご了承ください。 ■メール便は、1冊から送料無料です。※宅配便の場合、2,500円以上送料無料です。※最短翌日配達ご希望の方は、宅配便をご選択下さい。※「代引き」ご希望の方は宅配便をご選択下さい。※配送番号付きのゆうパケットをご希望の場合は、追跡可能メール便（送料210円）をご選択ください。■ただいま、オリジナルカレンダーをプレゼントしております。■お急ぎの方は「もったいない本舗　お急ぎ便店」をご利用ください。最短翌日配送、手数料298円から■まとめ買いの方は「もったいない本舗　おまとめ店」がお買い得です。■中古品ではございますが、良好なコンディションです。決済は、クレジットカード、代引き等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	1,074円
Secure Web Application Development A Hands-On Guide with Python and Django【電子書籍】[ Matthew Baker ] 楽天Kobo電子書籍ストア	＜p＞Cyberattacks are becoming more commonplace and the Open Web Application Security Project (OWASP), estimates 94% of sites have flaws in their access control alone. Attacks evolve to work around new defenses, and defenses must evolve to remain effective. Developers need to understand the fundamentals of attacks and defenses in order to comprehend new techniques as they become available. This book teaches you how to write secure web applications.＜/p＞＜p＞The focus is highlighting how hackers attack applications along with a broad arsenal of defenses. This will enable you to pick appropriate techniques to close vulnerabilities while still providing users with their needed functionality.＜/p＞＜p＞Topics covered include:＜/p＞＜p＞A framework for deciding what needs to be protected and how strongly＜/p＞＜p＞Configuring services such as databases and web servers＜/p＞＜p＞Safe use of HTTP methods such as GET, POST, etc, cookies and use of HTTPS＜/p＞＜p＞Safe REST APIs＜/p＞＜p＞Server-side attacks and defenses such as injection and cross-site scripting＜/p＞＜p＞Client-side attacks and defenses such as cross-site request forgery＜/p＞＜p＞Security techniques such as CORS, CSP＜/p＞＜p＞Password management, authentication and authorization, including OAuth2＜/p＞＜p＞Best practices for dangerous operations such as password change and reset＜/p＞＜p＞Use of third-party components and supply chain security (Git, CI/CD etc)＜/p＞＜p＞＜strong＞What You'll Learn＜/strong＞＜/p＞＜ul＞＜li＞＜/li＞＜li＞＜p＞Review the defenses that can used to prevent attacks＜/p＞＜/li＞＜li＞＜p＞Model risks to better understand what to defend and how＜/p＞＜/li＞＜li＞＜p＞Choose appropriate techniques to defend against attacks＜/p＞＜/li＞＜li＞＜p＞Implement defenses in Python/Django applications＜/p＞＜/li＞＜/ul＞＜p＞＜strong＞Who This Book Is For＜/strong＞＜/p＞＜ul＞＜li＞Developers who already know how to build web applications but need to know more about security＜/li＞＜li＞Non-professional software engineers, such as scientists, who must develop web tools and want to make their algorithms available to a wider audience.＜/li＞＜li＞Engineers and managers who are responsible for their product/company technical security policy＜/li＞＜/ul＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	7,292円
Deep Learning with PyTorch Lightning Swiftly build high-performance Artificial Intelligence (AI) models using Python【電子書籍】[ Kunal Sawarkar ] 楽天Kobo電子書籍ストア	＜p＞Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper Key Features ? Become well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domains ? Speed up your research using PyTorch Lightning by creating new loss functions, networks, and architectures ? Train and build new algorithms for massive data using distributed training Book Description PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implementing PyTorch Lightning models to get up to speed in no time. You'll start by learning how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. Next, you'll build a network and application from scratch and see how you can expand it based on your specific needs, beyond what the framework can provide. The book also demonstrates how to implement out-of-box capabilities to build and train Self-Supervised Learning, semi-supervised learning, and time series models using PyTorch Lightning. As you advance, you'll discover how generative adversarial networks (GANs) work. Finally, you'll work with deployment-ready applications, focusing on faster performance and scaling, model scoring on massive volumes of data, and model debugging. By the end of this PyTorch book, you'll have developed the knowledge and skills necessary to build and deploy your own scalable DL applications using PyTorch Lightning. What you will learn ? Customize models that are built for different datasets, model architectures, and optimizers ? Understand how a variety of Deep Learning models from image recognition and time series to GANs, semi-supervised and self-supervised models can be built ? Use out-of-the-box model architectures and pre-trained models using transfer learning ? Run and tune DL models in a multi-GPU environment using mixed-mode precisions ? Explore techniques for model scoring on massive workloads ? Discover troubleshooting techniques while debugging DL models Who this book is for This deep learning book is for citizen data scientists and expert data scientists transitioning from other frameworks to PyTorch Lightning. This book will also be useful for deep learning researchers who are just getting started with coding for deep learning models using PyTorch Lightning. Working knowledge of Python programming and an intermediate-level understanding of statistics and deep learning fundamentals is expected.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,739円
Practical Docker with Python Build, Release, and Distribute Your Python App with Docker【電子書籍】[ Sathyajith Bhat ] 楽天Kobo電子書籍ストア	＜p＞Learn the fundamentals of containerization and get acquainted with Docker. This second edition builds upon the foundation of the first book by revising all the chapters, updating the commands, code, and examples to meet the changes in Docker. It also introduces a new chapter on setting up your application for production deployment and breaks down terminologies like Dockerfile and Docker volumes while taking you on a guided tour of building a telegram bot using Python.＜/p＞＜p＞You'll start with a brief history of how containerization has changed over the years. Next, we look at how to install (including using the new WSL2 mode) and get started with Docker. The next couple of chapters will focus on understanding the Dockerfile, including the structure and the core instructions used in building a Docker image. You'll also see how to distribute Docker images using Docker hub and other private registries. From there, you'll look at using Docker volumes for persisting data. Then learn how to run multi-container applications with Docker compose and learn inter-container networking works with Docker networks. Finally, you'll look at how to prepare a containerized application for production deployments.＜/p＞＜p＞Throughout the book you'll apply the techniques learned through the chapters by building a Telegram messenger Chatbot and see how much easier Docker makes it possible to build, release, contribute and distribute an application. In addition, the book shows how optimize the Docker images for production servers by using multi-stage builds and improve the reliability of your services by using health checks and restart policies. ＜em＞Practical Docker with Python＜/em＞ will break down terminologies like Dockerfile and Docker volumes, and take you on a guided tour of building a telegram bot using Python.＜/p＞＜p＞＜strong＞What You'll Learn＜/strong＞＜/p＞＜ul＞＜li＞Compare the difference between containerization and virtualization＜/li＞＜li＞Understand the Dockerfile and converting your application to Docker image＜/li＞＜li＞Define and run multi-container applications with Docker compose＜/li＞＜li＞Review data persistency with Docker volumes＜/li＞＜/ul＞＜p＞＜strong＞Who This Book Is For＜/strong＞＜/p＞＜p＞Beginner and intermediate developers, DevOps practitioners who are looking improving their build and release workflow by containerizing applications as well as system administrators learning to implement DevOps principles.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	6,685円
Interpretable Machine Learning with Python Learn to build interpretable high-performance models with hands-on real-world examples【電子書籍】[ Serg Mas?s ] 楽天Kobo電子書籍ストア	＜p＞＜b＞A deep and detailed dive into the key aspects and challenges of machine learning interpretability, complete with the know-how on how to overcome and leverage them to build fairer, safer, and more reliable models＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Learn how to extract easy-to-understand insights from any machine learning model＜/li＞＜li＞Become well-versed with interpretability techniques to build fairer, safer, and more reliable models＜/li＞＜li＞Mitigate risks in AI systems before they have broader implications by learning how to debug black-box models＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Do you want to gain a deeper understanding of your models and better mitigate poor prediction risks associated with machine learning interpretation? If so, then Interpretable Machine Learning with Python deserves a place on your bookshelf. We’ll be starting off with the fundamentals of interpretability, its relevance in business, and exploring its key aspects and challenges. As you progress through the chapters, you'll then focus on how white-box models work, compare them to black-box and glass-box models, and examine their trade-off. You’ll also get you up to speed with a vast array of interpretation methods, also known as Explainable AI (XAI) methods, and how to apply them to different use cases, be it for classification or regression, for tabular, time-series, image or text. In addition to the step-by-step code, this book will also help you interpret model outcomes using examples. You’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability. The methods you’ll explore here range from state-of-the-art feature selection and dataset debiasing methods to monotonic constraints and adversarial retraining. By the end of this book, you'll be able to understand ML models better and enhance them through interpretability tuning. ＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Recognize the importance of interpretability in business＜/li＞＜li＞Study models that are intrinsically interpretable such as linear models, decision trees, and Na?ve Bayes＜/li＞＜li＞Become well-versed in interpreting models with model-agnostic methods＜/li＞＜li＞Visualize how an image classifier works and what it learns＜/li＞＜li＞Understand how to mitigate the influence of bias in datasets＜/li＞＜li＞Discover how to make models more reliable with adversarial robustness＜/li＞＜li＞Use monotonic constraints to make fairer and safer models＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is primarily written for data scientists, machine learning developers, and data stewards who find themselves under increasing pressures to explain the workings of AI systems, their impacts on decision making, and how they identify and manage bias. It’s also a useful resource for self-taught ML enthusiasts and beginners who want to go deeper into the subject matter, though a solid grasp on the Python programming language and ML fundamentals is needed to follow along.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,734円
Introduction to Machine Learning with Python A Guide for Data Scientists【電子書籍】[ Sarah Guido ] 楽天Kobo電子書籍ストア	＜p＞Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.＜/p＞＜p＞You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas M?ller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.＜/p＞＜p＞With this book, you’ll learn:＜/p＞＜ul＞＜li＞Fundamental concepts and applications of machine learning＜/li＞＜li＞Advantages and shortcomings of widely used machine learning algorithms＜/li＞＜li＞How to represent data processed by machine learning, including which data aspects to focus on＜/li＞＜li＞Advanced methods for model evaluation and parameter tuning＜/li＞＜li＞The concept of pipelines for chaining models and encapsulating your workflow＜/li＞＜li＞Methods for working with text data, including text-specific processing techniques＜/li＞＜li＞Suggestions for improving your machine learning and data science skills＜/li＞＜/ul＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,617円
Tkinter GUI Application Development Cookbook A practical solution to your GUI development problems with Python and Tkinter【電子書籍】[ Alejandro Rodas de Paz ] 楽天Kobo電子書籍ストア	＜p＞Discover solutions to all your Tkinter and Python GUI development problems About This Book ? Integrate efficient Python GUI programming techniques with Tkinter ? Efficiently implement advanced MVC architectures in your Python GUI apps ? Solve all your problems related to Tkinter and Python GUI development Who This Book Is For This book is for Python developers who are familiar with the basics of the language syntax, data structures, and OOP. You do not need previous experience with Tkinter or other GUI development libraries. What You Will Learn ? Add widgets and handle user events ? Lay out widgets within windows using frames and the different geometry managers ? Configure widgets so that they have a customized appearance and behavior ? Improve the navigation of your apps with menus and dialogs ? Apply object-oriented programming techniques in Tkinter applications ? Use threads to achieve responsiveness and update the GUI ? Explore the capabilities of the canvas widget and the types of items that can be added to it ? Extend Tkinter applications with the TTK (themed Tkinter) module In Detail As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions. Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background. You will then make your apps leverage network resources effectively, perform 2D and 3D animation-related tasks, create 3D objects, and perform advanced graphical operations. Finally, this book covers using the canvas and themed widgets. By the end of the book, you will have an in-depth knowledge of Tkinter classes, and will know how to use them to build efficient and rich GUI applications. Style and approach A practical recipe-based guide that will help you find solutions to all your Tkinter and Python GUI development-related problems.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,165円
【中古】 1981年のスワンソング / 五十嵐貴久 / 幻冬舎 [文庫]【メール便送料無料】【最短翌日配達対応】もったいない本舗　楽天市場店	著者：五十嵐貴久出版社：幻冬舎サイズ：文庫ISBN-10：434442672XISBN-13：9784344426726■こちらの商品もオススメです ● わるいやつら上巻改版 / 松本清張 / 新潮社 [文庫] ● わるいやつら下巻改版 / 松本清張 / 新潮社 [文庫] ● 眼の壁改版 / 松本清張 / 新潮社 [文庫] ● 幻獣少年キマイラ / 夢枕獏, 天野喜孝 / 朝日ソノラマ [文庫] ● 黄金の島下 / 真保裕一 / 講談社 [文庫] ● 黄金の島上 / 真保裕一 / 講談社 [文庫] ● 暖簾改版 / 山崎豊子 / 新潮社 [文庫] ● だれかのいとしいひと / 角田光代 / 文藝春秋 [文庫] ● 真田軍記改版 / 井上靖 / KADOKAWA [文庫] ● パパとムスメの7日間 / 五十嵐貴久 / 幻冬舎 [文庫] ● 2005年のロケットボーイズ / 五十嵐貴久 / 双葉社 [文庫] ● いつまでも白い羽根 / 藤岡陽子 / 光文社 [その他] ● 君の膵臓をたべたい / 住野よる / 双葉社 [文庫] ● 誘拐新装改版 / 五十嵐貴久 / 双葉社 [文庫] ● パパママムスメの10日間 / 五十嵐貴久 / 幻冬舎 [文庫] ■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　発送まで48時間かかる場合があります。あらかじめご了承ください。 ■メール便は、1冊から送料無料です。※宅配便の場合、2,500円以上送料無料です。※最短翌日配達ご希望の方は、宅配便をご選択下さい。※「代引き」ご希望の方は宅配便をご選択下さい。※配送番号付きのゆうパケットをご希望の場合は、追跡可能メール便（送料210円）をご選択ください。■ただいま、オリジナルカレンダーをプレゼントしております。■お急ぎの方は「もったいない本舗　お急ぎ便店」をご利用ください。最短翌日配送、手数料298円から■まとめ買いの方は「もったいない本舗　おまとめ店」がお買い得です。■中古品ではございますが、良好なコンディションです。決済は、クレジットカード、代引き等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	546円
【中古】あいしていると言ってみろ！ / 高峰顕 / リブレ [コミック]【メール便送料無料】【最短翌日配達対応】もったいない本舗　楽天市場店	著者：高峰顕出版社：リブレサイズ：コミックISBN-10：4799742493ISBN-13：9784799742495■こちらの商品もオススメです ● 何かいいの見つけた！ / ひなこ / 大洋図書 [コミック] ● 先生なんて嫌いです。 / ひなこ / 大洋図書 [コミック] ● 僕のおまわりさん / にやま / 竹書房 [コミック] ● 純情ビッチ、ハツコイ系 / おわる / 竹書房 [コミック] ● 恋する絶滅遺伝子Ω / 新書館 [コミック] ● ムカつく同僚とセフレになりました / U / 竹書房 [コミック] ● 猫かわいがりは禁止です / 香坂あきほ / KADOKAWA [コミック] ● このΩ、24時間守られてます / 小鴨 / 三交社 [コミック] ● いとおしき日々 / sono.N / 三交社 [コミック] ● つわもののお気に召すまま / コアマガジン [コミック] ● ふたりの息子に狙われています / 佳門サエコ / 新書館 [コミック] ● 恋人は霊感性年 / 五月女えむ / マガジン・マガジン [コミック] ● お隣さんちの双子くん / アベコ / 幻冬舎コミックス [コミック] ● 溺れるカラダは恋のせい！？ / 高峰顕 / リブレ出版 [コミック] ● 君を瞳に映さない / リブレ [コミック] ■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　発送まで48時間かかる場合があります。あらかじめご了承ください。 ■メール便は、1冊から送料無料です。※宅配便の場合、2,500円以上送料無料です。※最短翌日配達ご希望の方は、宅配便をご選択下さい。※「代引き」ご希望の方は宅配便をご選択下さい。※配送番号付きのゆうパケットをご希望の場合は、追跡可能メール便（送料210円）をご選択ください。■ただいま、オリジナルカレンダーをプレゼントしております。■お急ぎの方は「もったいない本舗　お急ぎ便店」をご利用ください。最短翌日配送、手数料298円から■まとめ買いの方は「もったいない本舗　おまとめ店」がお買い得です。■中古品ではございますが、良好なコンディションです。決済は、クレジットカード、代引き等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	328円
Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition【電子書籍】[ Joseph Howse ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical code＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Build powerful computer vision applications in concise code with OpenCV 4 and Python 3＜/li＞＜li＞Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking＜/li＞＜li＞Train, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networks＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 4 and Python 3.＜/p＞＜p＞You'll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you'll have opportunities for hands-on activities. Next, you'll tackle two popular challenges: face detection and face recognition. You'll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you'll develop your skills in 3D tracking and augmented reality. Finally, you'll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age.＜/p＞＜p＞By the end of this book, you'll have the skills you need to execute real-world computer vision projects.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Install and familiarize yourself with OpenCV 4's Python 3 bindings＜/li＞＜li＞Understand image processing and video analysis basics＜/li＞＜li＞Use a depth camera to distinguish foreground and background regions＜/li＞＜li＞Detect and identify objects, and track their motion in videos＜/li＞＜li＞Train and use your own models to match images and classify objects＜/li＞＜li＞Detect and recognize faces, and classify their gender and age＜/li＞＜li＞Build an augmented reality application to track an image in 3D＜/li＞＜li＞Work with machine learning models, including SVMs, artificial neural networks (ANNs), and deep neural networks (DNNs)＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞If you are interested in learning computer vision, machine learning, and OpenCV in the context of practical real-world applications, then this book is for you. This OpenCV book will also be useful for anyone getting started with computer vision as well as experts who want to stay up-to-date with OpenCV 4 and Python 3. Although no prior knowledge of image processing, computer vision or machine learning is required, familiarity with basic Python programming is a must.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,739円
Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter【電子書籍】[ Silas Toms ] 楽天Kobo電子書籍ストア	＜p＞Explore GIS processing and learn to work with various tools and libraries in Python. About This Book ? Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas ? Leverage new ArcGIS API to process geospatial data for the cloud. ? Explore various Python geospatial web and machine learning frameworks. Who This Book Is For The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3. What You Will Learn ? Manage code libraries and abstract geospatial analysis techniques using Python 3. ? Explore popular code libraries that perform specific tasks for geospatial analysis. ? Utilize code libraries for data conversion, data management, web maps, and REST API creation. ? Learn techniques related to processing geospatial data in the cloud. ? Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite. In Detail Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API. Style and approach The book takes a practical, example-driven approach to teach you GIS analysis and automation techniques with Python 3.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	6,313円
Generative AI with Python and TensorFlow 2 Create images, text, and music with VAEs, GANs, LSTMs, Transformer models【電子書籍】[ Joseph Babcock ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Fun and exciting projects to learn what artificial minds can create＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along＜/li＞＜li＞Look inside the most famous deep generative models, from GPT to MuseGAN＜/li＞＜li＞Learn to build and adapt your own models in TensorFlow 2.x＜/li＞＜li＞Explore exciting, cutting-edge use cases for deep generative AI＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI?＜/p＞＜p＞In this book, you'll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You'll learn how to implement models yourself in TensorFlow and get to grips with the latest research on deep neural networks.＜/p＞＜p＞There's been an explosion in potential use cases for generative models. You'll look at Open AI's news generator, deepfakes, and training deep learning agents to navigate a simulated environment.＜/p＞＜p＞Recreate the code that's under the hood and uncover surprising links between text, image, and music generation.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Export the code from GitHub into Google Colab to see how everything works for yourself＜/li＞＜li＞Compose music using LSTM models, simple GANs, and MuseGAN＜/li＞＜li＞Create deepfakes using facial landmarks, autoencoders, and pix2pix GAN＜/li＞＜li＞Learn how attention and transformers have changed NLP＜/li＞＜li＞Build several text generation pipelines based on LSTMs, BERT, and GPT-2＜/li＞＜li＞Implement paired and unpaired style transfer with networks like StyleGAN＜/li＞＜li＞Discover emerging applications of generative AI like folding proteins and creating videos from images＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This is a book for Python programmers who are keen to create and have some fun using generative models. To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,160円
【中古】あいしていると言ってみろ！ / 高峰顕 / リブレ [コミック]【宅配便出荷】もったいない本舗　おまとめ店	著者：高峰顕出版社：リブレサイズ：コミックISBN-10：4799742493ISBN-13：9784799742495■こちらの商品もオススメです ● 何かいいの見つけた！ / ひなこ / 大洋図書 [コミック] ● 先生なんて嫌いです。 / ひなこ / 大洋図書 [コミック] ● 僕のおまわりさん / にやま / 竹書房 [コミック] ● 純情ビッチ、ハツコイ系 / おわる / 竹書房 [コミック] ● 恋する絶滅遺伝子Ω / 新書館 [コミック] ● ムカつく同僚とセフレになりました / U / 竹書房 [コミック] ● 猫かわいがりは禁止です / 香坂あきほ / KADOKAWA [コミック] ● このΩ、24時間守られてます / 小鴨 / 三交社 [コミック] ● いとおしき日々 / sono.N / 三交社 [コミック] ● つわもののお気に召すまま / コアマガジン [コミック] ● ふたりの息子に狙われています / 佳門サエコ / 新書館 [コミック] ● 恋人は霊感性年 / 五月女えむ / マガジン・マガジン [コミック] ● お隣さんちの双子くん / アベコ / 幻冬舎コミックス [コミック] ● 溺れるカラダは恋のせい！？ / 高峰顕 / リブレ出版 [コミック] ● 君を瞳に映さない / リブレ [コミック] ■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　発送まで72時間かかる場合があります。あらかじめご了承ください。■宅配便(送料398円)にて出荷致します。合計3980円以上は送料無料。■ただいま、オリジナルカレンダーをプレゼントしております。■送料無料の「もったいない本舗本店」もご利用ください。メール便送料無料です。■お急ぎの方は「もったいない本舗　お急ぎ便店」をご利用ください。最短翌日配送、手数料298円から■中古品ではございますが、良好なコンディションです。決済はクレジットカード等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	278円
【中古】 QLAP! (クラップ) 2020年 07月号 [雑誌] / 音楽と人 [雑誌]【宅配便出荷】もったいない本舗　おまとめ店	出版社：音楽と人JANコード：4910032470701■こちらの商品もオススメです ● Myojo (ミョウジョウ) 2021年 02月号 [雑誌] / 集英社 [雑誌] ● TVガイドPLUS vol．36（2019　AUT / 東京ニュース通信社 [ムック] ● ポポロ 2016年 02月号 [雑誌] / 麻布台出版社 [雑誌] ● TVガイドPLUS vol．38（2020　SPR / 東京ニュース通信社 [ムック] ● TVnavi SMILE (テレビナビスマイル) 2018年 11月号 [雑誌] / 日本工業新聞社 [雑誌] ● 日経エンタテインメント! 2019年 09月号 [雑誌] / 日経BP [雑誌] ● 月刊 TVガイド関東版 2020年 09月号 [雑誌] / 東京ニュース通信社 [雑誌] ● 週刊ザテレビジョン首都圏版 2021年 1/1号 [雑誌] / KADOKAWA [雑誌] ● non・no(ノンノ) 2020年 02月号 [雑誌] / 集英社 [雑誌] ● Myojo (ミョウジョウ) 2020年 01月号 [雑誌] / 集英社 [雑誌] ● TVnavi SMILE (テレビナビスマイル) 2020年 09月号 [雑誌] / 日本工業新聞社 [雑誌] ● Wink up (ウィンクアップ) 2020年 09月号 [雑誌] / ワニブックス [雑誌] ● QLAP! (クラップ) 2020年 02月号 [雑誌] / 音楽と人 [雑誌] ● TVfan cross (テレビファンクロス) Vol.30 2019年 05月号 [雑誌] / メディアボーイ [雑誌] ● anan (アンアン) 2020年 4/1号 [雑誌] / マガジンハウス [雑誌] ■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　発送まで72時間かかる場合があります。あらかじめご了承ください。■宅配便(送料398円)にて出荷致します。合計3980円以上は送料無料。■ただいま、オリジナルカレンダーをプレゼントしております。■送料無料の「もったいない本舗本店」もご利用ください。メール便送料無料です。■お急ぎの方は「もったいない本舗　お急ぎ便店」をご利用ください。最短翌日配送、手数料298円から■中古品ではございますが、良好なコンディションです。決済はクレジットカード等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	208円
Coding with Python - Create Amazing Graphics【電子書籍】[ Max Wainewright ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Coding with Python ? Create Amazing Graphics＜/strong＞ introduces coding in Python through a variety of projects. Each one teaches new coding concepts and results in some amazing graphics.＜/p＞＜p＞Python is a powerful, text-based programming language essential to grasp for serious coding but can be dull to learn. This book focuses on inspired learning. Step-by-step, it illustrates how to use Python code to create exciting and colourful graphics ー making learning Python great fun!＜/p＞＜p＞Learn Python code to:＜/p＞＜ul＞＜li＞Use random numbers to create unique artwork＜/li＞＜li＞Mix colours together using variables to create amazing effects＜/li＞＜li＞Use loops to repeat your code and create intricate patterns＜/li＞＜li＞Code your own functions and build up your own designs＜/li＞＜/ul＞＜p＞＜strong＞Table of Contents＜/strong＞＜/p＞＜p＞＜strong＞Getting Started＜/strong＞＜/p＞＜p＞Saying Hello＜br /＞ Giant Circles＜br /＞ Simple Squares＜br /＞ Square Patterns＜br /＞ Multi Patterns＜br /＞ Spinning Circles＜/p＞＜p＞＜strong＞A Bit Random＜/strong＞＜/p＞＜p＞Random Dots＜br /＞ Random Colours＜br /＞ Random Lines＜br /＞ Random Sizes＜br /＞ Random Line Burst＜br /＞ Random Colour Spin＜br /＞ Random Hoops＜/p＞＜p＞＜strong＞Mixing Colours＜/strong＞＜/p＞＜p＞Blended Square＜br /＞ Blended Circle＜br /＞ Shaded Sphere＜br /＞ Colour Mix Points＜br /＞ Spiral Blend＜br /＞ Colour List Spiral＜/p＞＜p＞＜strong＞Drawing Pictures＜/strong＞＜/p＞＜p＞Flower＜br /＞ Donut＜br /＞ Pizza＜br /＞ Emojis＜br /＞ Dog＜/p＞＜p＞＜strong＞Functions＜/strong＞＜/p＞＜p＞Square Function＜br /＞ Flower Function＜br /＞ Recursive Spiral＜br /＞ Recursive Squares＜br /＞ Recursive Tree＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	2,193円
【中古】エスパー魔美 4 / 藤子・F・不二雄 / 小学館 [コミック]【メール便送料無料】【最短翌日配達対応】もったいない本舗　楽天市場店	著者：藤子・F・不二雄出版社：小学館サイズ：コミックISBN-10：4091423183ISBN-13：9784091423184■こちらの商品もオススメです ● エスパー魔美 3 / 藤子・F・不二雄 / 小学館 [コミック] ● エスパー魔美 2 / 藤子・F・不二雄 / 小学館 [コミック] ● エスパー魔美 1 / 藤子・F・不二雄 / 小学館 [コミック] ● エスパー魔美 5 / 藤子・F・不二雄 / 小学館 [コミック] ● エスパー魔美 7 / 小学館 [コミック] ● クレヨンしんちゃんのまんがお仕事おもしろ百科まんがでわかるお仕事のあれこれ新版 / 双葉社 [単行本（ソフトカバー）] ● 食物連鎖/CD/FLCG-3023 / 中谷美紀 / フォーライフミュージックエンタテイメント [CD] ■通常24時間以内に出荷可能です。※繁忙期やセール等、ご注文数が多い日につきましては　発送まで48時間かかる場合があります。あらかじめご了承ください。 ■メール便は、1冊から送料無料です。※宅配便の場合、2,500円以上送料無料です。※最短翌日配達ご希望の方は、宅配便をご選択下さい。※「代引き」ご希望の方は宅配便をご選択下さい。※配送番号付きのゆうパケットをご希望の場合は、追跡可能メール便（送料210円）をご選択ください。■ただいま、オリジナルカレンダーをプレゼントしております。■お急ぎの方は「もったいない本舗　お急ぎ便店」をご利用ください。最短翌日配送、手数料298円から■まとめ買いの方は「もったいない本舗　おまとめ店」がお買い得です。■中古品ではございますが、良好なコンディションです。決済は、クレジットカード、代引き等、各種決済方法がご利用可能です。■万が一品質に不備が有った場合は、返金対応。■クリーニング済み。■商品画像に「帯」が付いているものがありますが、中古品のため、実際の商品には付いていない場合がございます。■商品状態の表記につきまして・非常に良い：　　使用されてはいますが、　　非常にきれいな状態です。　　書き込みや線引きはありません。・良い：　　比較的綺麗な状態の商品です。　　ページやカバーに欠品はありません。　　文章を読むのに支障はありません。・可：　　文章が問題なく読める状態の商品です。　　マーカーやペンで書込があることがあります。　　商品の痛みがある場合があります。	534円
OpenCV 4 with Python Blueprints Build creative computer vision projects with the latest version of OpenCV 4 and Python 3, 2nd Edition【電子書籍】[ Dr. Menua Gevorgyan ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworks＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Understand how to capture high-quality image data, detect and track objects, and process the actions of animals or humans＜/li＞＜li＞Implement your learning in different areas of computer vision＜/li＞＜li＞Explore advanced concepts in OpenCV such as machine learning, artificial neural network, and augmented reality＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞OpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks.＜/p＞＜p＞You'll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you'll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you'll understand how to align images, and detect and track objects using neural networks.＜/p＞＜p＞By the end of this OpenCV Python book, you'll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Generate real-time visual effects using filters and image manipulation techniques such as dodging and burning＜/li＞＜li＞Recognize hand gestures in real-time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor＜/li＞＜li＞Learn feature extraction and feature matching to track arbitrary objects of interest＜/li＞＜li＞Reconstruct a 3D real-world scene using 2D camera motion and camera reprojection techniques＜/li＞＜li＞Detect faces using a cascade classifier and identify emotions in human faces using multilayer perceptrons＜/li＞＜li＞Classify, localize, and detect objects with deep neural networks＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for intermediate-level OpenCV users who are looking to enhance their skills by developing advanced applications. Familiarity with OpenCV concepts and Python libraries, and basic knowledge of the Python programming language are assumed.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,877円
Artificial Intelligence Programming with Python: From Zero to Hero ARTIFICIAL INTELLIGENCE PROGRA [ Perry Xiao ] 楽天ブックス	ARTIFICIAL INTELLIGENCE PROGRA Perry Xiao WILEY2022 Paperback English ISBN：9781119820864 洋書 Computers & Science（コンピューター＆科学） Computers	6,336円
Learn OpenCV 4.5 with Python 3.7 by Examples Implement Computer Vision Algorithms Provided by OpenCV with Python for Image Processing, Object Detection and Machine Learning【電子書籍】[ James Chen ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞What This Book is About＜/strong＞＜/p＞＜p＞When you searched for this book, you have already known the importance of the OpenCV/Python in the fields of computer vision, image processing and machine learning. This book begins with step-by-step instructions of installation as well as a simple Hello World, then gets into the OpenCV Basics, Image Processing, Object Detection and finally Machine Learning.＜/p＞＜p＞＜strong＞Key Features＜/strong＞＜/p＞＜p＞Example for every topic, all the source codes are available in Github.＜/p＞＜p＞Line by line explanation of the source codes.＜/p＞＜p＞Focus mainly on implementation of algorithms, rather than mathematical theories.＜/p＞＜p＞＜strong＞Whom This Book Is For＜/strong＞＜/p＞＜p＞This book is for people with a variety of computer programming levels, from those with very limited knowledge of computer vision to the experienced ones. The readers do not need to have previous experiences of Python/OpenCV. No matter you are a beginner or experienced programmer, as long as you want to learn OpenCV with Python, you will benefit from this book.＜/p＞＜p＞＜strong＞Table of Contents＜/strong＞＜/p＞＜p＞＜strong＞1. Introduction＜/strong＞＜/p＞＜ol＞＜li＞What Is OpenCV＜/li＞＜li＞Whom This Book Is For＜/li＞＜li＞How to Get the Source Codes for This Book＜/li＞＜li＞Hardware Requirements and Software Versions＜/li＞＜li＞How This Book Is Organized＜/li＞＜/ol＞＜p＞＜strong＞2. Installation＜/strong＞＜/p＞＜ol＞＜li＞Install on Windows＜/li＞＜li＞Install Python on Ubuntu＜/li＞＜li＞Configure PyCharm and Install OpenCV＜/li＞＜/ol＞＜p＞＜strong＞3. OpenCV Basics＜/strong＞＜/p＞＜ol＞＜li＞Load and Display Images＜/li＞＜li＞Load and Display Videos＜/li＞＜li＞Display Webcam＜/li＞＜li＞Play Youtube Video＜/li＞＜li＞Image Fundamentals＜/li＞＜li＞Draw Shapes＜/li＞＜li＞Draw Texts＜/li＞＜li＞Draw an OpenCV-like Icon＜/li＞＜/ol＞＜p＞＜strong＞4. User Interaction＜/strong＞＜/p＞＜ol＞＜li＞Mouse Operations＜/li＞＜li＞Draw Circles with Mouse＜/li＞＜li＞Draw Polygon with Mouse＜/li＞＜li＞Crop an Image with Mouse＜/li＞＜li＞Input Values with Trackbars＜/li＞＜/ol＞＜p＞＜strong＞5. Image Processing＜/strong＞＜/p＞＜ol＞＜li＞Change Color Spaces＜/li＞＜li＞Resize, Crop and Rotate an Image＜/li＞＜li＞Adjust Contrast and Brightness of an Image＜/li＞＜li＞Adjust Hue, Saturation and Value＜/li＞＜li＞Blend Image＜/li＞＜li＞Bitwise Operation＜/li＞＜li＞Warp Image＜/li＞＜li＞Blur Image＜/li＞＜li＞Histogram＜/li＞＜/ol＞＜p＞＜strong＞6. Object Detection＜/strong＞＜/p＞＜ol＞＜li＞Canny Edge Detection＜/li＞＜li＞Dilation and Erosion＜/li＞＜li＞Shape Detection＜/li＞＜li＞Color Detection＜/li＞＜li＞Text Recognition with Tesseract＜/li＞＜li＞Human Detection＜/li＞＜li＞Face and Eye Detection＜/li＞＜li＞Remove Background＜/li＞＜li＞Blur Background＜/li＞＜/ol＞＜p＞＜strong＞7. Machine Learning＜/strong＞＜/p＞＜ol＞＜li＞K-Means Clustering＜/li＞＜li＞K-Nearest Neighbors＜/li＞＜li＞Support Vector Machine＜/li＞＜li＞Artificial Neural Network (ANN)＜/li＞＜/ol＞＜p＞＜strong＞About the Author＜/strong＞＜/p＞＜p＞＜strong＞Index＜/strong＞＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	2,280円
機械学習のためのカーネル100問with Python[本/雑誌] (機械学習の数理100問シリーズ) / 鈴木讓/著ネオウィング楽天市場店	ご注文前に必ずご確認ください＜商品説明＞話題沸騰!阪大教授Joe Suzukiが講義の演習問題を書籍化。プログラムと例で、カーネルの苦手を克服!＜収録内容＞第1章正定値カーネル第2章 Hilbert空間第3章再生核Hilbert空間第4章カーネル計算の実際第5章 MMDとHSIC第6章 Gauss過程と関数データ解析＜商品詳細＞商品番号：NEOBK-2693227Suzuki Yuzuru / Cho / Kikai Gakushu No Tame No Kernel 100 Mon with Python (Kikai Gakushu No Suri 100 Mon Series)メディア：本/雑誌重量：492g発売日：2021/12JAN：9784320125131機械学習のためのカーネル100問with Python[本/雑誌] (機械学習の数理100問シリーズ) / 鈴木讓/著2021/12発売	3,300円
Hands-On Genetic Algorithms with Python Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems【電子書籍】[ Eyal Wirsansky ] 楽天Kobo電子書籍ストア	＜p＞＜b＞Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Explore the ins and outs of genetic algorithms with this fast-paced guide＜/li＞＜li＞Implement tasks such as feature selection, search optimization, and cluster analysis using Python＜/li＞＜li＞Solve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applications＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence. After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications. By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Understand how to use state-of-the-art Python tools to create genetic algorithm-based applications＜/li＞＜li＞Use genetic algorithms to optimize functions and solve planning and scheduling problems＜/li＞＜li＞Enhance the performance of machine learning models and optimize deep learning network architecture＜/li＞＜li＞Apply genetic algorithms to reinforcement learning tasks using OpenAI Gym＜/li＞＜li＞Explore how images can be reconstructed using a set of semi-transparent shapes＜/li＞＜li＞Discover other bio-inspired techniques, such as genetic programming and particle swarm optimization＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,304円