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| 商品 | 説明 | 価格 |
|---|---|---|
 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。 | 4,993円 |
 Architecture Patterns with Python Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices【電子書籍】[ Harry Percival ] 楽天Kobo電子書籍ストア | ＜p＞As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are taking an interest in high-level software design patterns such as hexagonal/clean architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn’t always straightforward.＜/p＞ ＜p＞With this hands-on guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexityーand get the most value out of their test suites.＜/p＞ ＜p＞Each pattern is illustrated with concrete examples in beautiful, idiomatic Python, avoiding some of the verbosity of Java and C# syntax. Patterns include:＜/p＞ ＜ul＞ ＜li＞Dependency inversion and its links to ports and adapters (hexagonal/clean architecture)＜/li＞ ＜li＞Domain-driven design’s distinction between Entities, Value Objects, and Aggregates＜/li＞ ＜li＞Repository and Unit of Work patterns for persistent storage＜/li＞ ＜li＞Events, commands, and the message bus＜/li＞ ＜li＞Command-query responsibility segregation (CQRS)＜/li＞ ＜li＞Event-driven architecture and reactive microservices＜/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 |
 Edge Computing with Python End-to-end Edge Applications, Python Tools and Techniques, Edge Architectures, and AI Benefits (English Edition)【電子書籍】[ Abhinandan Bhadauria ] 楽天Kobo電子書籍ストア | ＜p＞The success of IoT and Industry 4.0 depends on edge computing and better network performance. The book, ‘Edge Computing with Python,’ intends to provide a fully-connected embedded environment in which readers can experience the applications of edge computing and IoT in a professional context. In this book, readers will learn what edge computing is, what its possible applications are, and how advantageous it is. This book provides thorough instructions for using Python to build every potential edge application. The book begins by configuring the programming environment with tools like VS Code, Python, and several popular libraries like SciPy, NumPy, and Pandas. Then, the book explains gaining access to IO devices, data handling, data storage, cloud connectivity, and hosting ready and pre-trained machine learning models step by step. The book delves into sophisticated ideas such as Docker Containers, MQTT, and FIWARE and how one can use them to construct Edge applications. In addition, the book details the Siemens Edge computing platform and how to use it for rapidly developing Edge applications. After reading this book, knowledge of Edge Computing's architecture, its benefits, and drawbacks will give readers a competitive advantage in the market.＜/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。 | 1,597円 |
 Data Visualization with Python Exploring Matplotlib, Seaborn, and Bokeh for Interactive Visualizations (English Edition)【電子書籍】[ Dr. Pooja ] 楽天Kobo電子書籍ストア | ＜p＞Python is a popular programming language for data visualization due to its rich ecosystem of libraries and tools. If you're interested in delving into data visualization in Python, this book is an excellent resource to begin your journey. With Matplotlib, you'll master the art of creating a wide range of charts, plots, and graphs. From basic line plots to complex 3D visualizations, you'll learn how to transform raw data into engaging visuals that tell compelling stories. Dive into Seaborn, a high-level library built on top of Matplotlib, and discover how to effortlessly create beautiful and informative statistical visualizations effortlessly. From heatmaps to distribution plots, you'll unleash the full potential of Seaborn in your data analysis endeavors. Lastly, you will learn how to unleash the true potential of Bokeh and create compelling data visualizations that allow users to explore and interact with data dynamically. By the end of the book, you will have acquired the knowledge and skills necessary to create a diverse range of visualizations proficiently.＜/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。 | 2,132円 |
 Learning Genetic Algorithms with Python Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition)【電子書籍】[ Ivan Gridin ] 楽天Kobo電子書籍ストア | ＜p＞Genetic algorithms are one of the most straightforward and powerful techniques used in machine learning. This book ‘Learning Genetic Algorithms with Python’ guides the reader right from the basics of genetic algorithms to its real practical implementation in production environments. Each of the chapters gives the reader an intuitive understanding of each concept. You will learn how to build a genetic algorithm from scratch and implement it in real-life problems. Covered with practical illustrated examples, you will learn to design and choose the best model architecture for the particular tasks. Cutting edge examples like radar and football manager problem statements, you will learn to solve high-dimensional big data challenges with ways of optimizing genetic algorithms.＜/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。 | 1,597円 |
 Hands-On Penetration Testing with Python Enhance your ethical hacking skills to build automated and intelligent systems【電子書籍】[ Furqan Khan ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞Implement defensive techniques in your ecosystem successfully with Python＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Identify and expose vulnerabilities in your infrastructure with Python＜/li＞ ＜li＞Learn custom exploit development .＜/li＞ ＜li＞Make robust and powerful cybersecurity tools with Python＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers.＜/p＞ ＜p＞Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you'll explore the advanced uses of Python in the domain of penetration testing and optimization. You'll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you'll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python.＜/p＞ ＜p＞By the end of this book, you'll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits.＜/p＞ ＜h4＞What you will learn＜/h4＞ ＜ul＞ ＜li＞Get to grips with Custom vulnerability scanner development＜/li＞ ＜li＞Familiarize yourself with web application scanning automation and exploit development＜/li＞ ＜li＞Walk through day-to-day cybersecurity scenarios that can be automated with Python＜/li＞ ＜li＞Discover enterprise-or organization-specific use cases and threat-hunting automation＜/li＞ ＜li＞Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows.＜/li＞ ＜li＞Understand web scraping in Python and use it for processing web responses＜/li＞ ＜li＞Explore Security Operations Centre (SOC) use cases＜/li＞ ＜li＞Get to understand Data Science, Python, and cybersecurity all under one hood＜/li＞ ＜/ul＞ ＜h4＞Who this book is for＜/h4＞ ＜p＞If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .＜/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。 | 3,290円 |
 Modern Time Series Forecasting with Python Explore industry-ready time series forecasting using modern machine learning and deep learning【電子書籍】[ Manu Joseph ] 楽天Kobo電子書籍ストア | ＜p＞＜b＞Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Explore industry-tested machine learning techniques used to forecast millions of time series＜/li＞＜li＞Get started with the revolutionary paradigm of global forecasting models＜/li＞＜li＞Get to grips with new concepts by applying them to real-world datasets of energy forecasting＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞We live in a serendipitous era where the explosion in the quantum of data collected and a renewed interest in data-driven techniques such as machine learning (ML), has changed the landscape of analytics, and with it, time series forecasting. This book, filled with industry-tested tips and tricks, takes you beyond commonly used classical statistical methods such as ARIMA and introduces to you the latest techniques from the world of ML. This is a comprehensive guide to analyzing, visualizing, and creating state-of-the-art forecasting systems, complete with common topics such as ML and deep learning (DL) as well as rarely touched-upon topics such as global forecasting models, cross-validation strategies, and forecast metrics. You’ll begin by exploring the basics of data handling, data visualization, and classical statistical methods before moving on to ML and DL models for time series forecasting. This book takes you on a hands-on journey in which you’ll develop state-of-the-art ML (linear regression to gradient-boosted trees) and DL (feed-forward neural networks, LSTMs, and transformers) models on a real-world dataset along with exploring practical topics such as interpretability. By the end of this book, you’ll be able to build world-class time series forecasting systems and tackle problems in the real world.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Find out how to manipulate and visualize time series data like a pro＜/li＞＜li＞Set strong baselines with popular models such as ARIMA＜/li＞＜li＞Discover how time series forecasting can be cast as regression＜/li＞＜li＞Engineer features for machine learning models for forecasting＜/li＞＜li＞Explore the exciting world of ensembling and stacking models＜/li＞＜li＞Get to grips with the global forecasting paradigm＜/li＞＜li＞Understand and apply state-of-the-art DL models such as N-BEATS and Autoformer＜/li＞＜li＞Explore multi-step forecasting and cross-validation strategies＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞The book is for data scientists, data analysts, machine learning engineers, and Python developers who want to build industry-ready time series models. Since the book explains most concepts from the ground up, basic proficiency in Python is all you need. Prior understanding of machine learning or forecasting will help speed up your learning. For experienced machine learning and forecasting practitioners, this book has a lot to offer in terms of advanced techniques and traversing the latest research frontiers in time series forecasting.＜/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。 | 4,563円 |
 Network Science with Python Explore the networks around us using network science, social network analysis, and machine learning【電子書籍】[ David Knickerbocker ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞Discover the use of graph networks to develop a new approach to data science using theoretical and practical methods with this expert guide using Python, printed in color＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Create networks using data points and information＜/li＞ ＜li＞Learn to visualize and analyze networks to better understand communities＜/li＞ ＜li＞Explore the use of network data in both - supervised and unsupervised machine learning projects＜/li＞ ＜li＞Purchase of the print or Kindle book includes a free PDF eBook＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard ? practical data sets. You'll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You'll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you'll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You'll also explore network analysis concepts, from basics to an advanced level.＜/p＞ ＜p＞By the end of the book, you'll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.＜/p＞ ＜h4＞What you will learn＜/h4＞ ＜ul＞ ＜li＞Explore NLP, network science, and social network analysis＜/li＞ ＜li＞Apply the tech stack used for NLP, network science, and analysis＜/li＞ ＜li＞Extract insights from NLP and network data＜/li＞ ＜li＞Generate personalized NLP and network projects＜/li＞ ＜li＞Authenticate and scrape tweets, connections, the web, and data streams＜/li＞ ＜li＞Discover the use of network data in machine learning projects＜/li＞ ＜/ul＞ ＜h4＞Who this book is for＜/h4＞ ＜p＞Network Science with Python demonstrates how programming and social science can be combined to find new insights. Data scientists, NLP engineers, software engineers, social scientists, and data science students will find this book useful. An intermediate level of Python programming is a prerequisite. Readers from both ? social science and programming backgrounds will find a new perspective and add a feather to their hat.＜/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。 | 4,540円 |
 Hands-On Image Processing with Python Expert techniques for advanced image analysis and effective interpretation of image data【電子書籍】[ Sandipan Dey ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks.＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Practical coverage of every image processing task with popular Python libraries＜/li＞ ＜li＞Includes topics such as pseudo-coloring, noise smoothing, computing image descriptors＜/li＞ ＜li＞Covers popular machine learning and deep learning techniques for complex image processing tasks＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python.＜/p＞ ＜p＞The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing.＜/p＞ ＜p＞By the end of this book, we will have learned to implement various algorithms for efficient image processing.＜/p＞ ＜h4＞What you will learn＜/h4＞ ＜ul＞ ＜li＞Perform basic data pre-processing tasks such as image denoising and spatial filtering in Python＜/li＞ ＜li＞Implement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in Python＜/li＞ ＜li＞Do morphological image processing and segment images with different algorithms＜/li＞ ＜li＞Learn techniques to extract features from images and match images＜/li＞ ＜li＞Write Python code to implement supervised / unsupervised machine learning algorithms for image processing＜/li＞ ＜li＞Use deep learning models for image classification, segmentation, object detection and style transfer＜/li＞ ＜/ul＞ ＜h4＞Who this book is for＜/h4＞ ＜p＞This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques 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。 | 4,085円 |
 Data Labeling in Machine Learning with Python Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models【電子書籍】[ Vijaya Kumar Suda ] 楽天Kobo電子書籍ストア | ＜p＞＜b＞Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Generate labels for regression in scenarios with limited training data＜/li＞＜li＞Apply generative AI and large language models (LLMs) to explore and label text data＜/li＞＜li＞Leverage Python libraries for image, video, and audio data analysis and data labeling＜/li＞＜li＞Purchase of the print or Kindle book includes a free PDF eBook＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Data labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data＜/li＞＜li＞Understand how to use Python libraries to apply rules to label raw data＜/li＞＜li＞Discover data augmentation techniques for adding classification labels＜/li＞＜li＞Leverage K-means clustering to classify unsupervised data＜/li＞＜li＞Explore how hybrid supervised learning is applied to add labels for classification＜/li＞＜li＞Master text data classification with generative AI＜/li＞＜li＞Detect objects and classify images with OpenCV and YOLO＜/li＞＜li＞Uncover a range of techniques and resources for data annotation＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.＜/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 |
 Machine Learning with Spark and Python Essential Techniques for Predictive Analytics【電子書籍】[ Michael Bowles ] 楽天Kobo電子書籍ストア | ＜p＞＜em＞Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition＜/em＞ simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Sparkーa ML framework from the Apache foundation. By implementing Spark, machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code.＜/p＞ ＜p＞＜em＞Machine Learning with Spark and Python＜/em＞ focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers many use cases such as what ad to place on a web page, predicting prices in securities markets, or detecting credit card fraud. The focus on two families gives enough room for full descriptions of the mechanisms at work in the algorithms. Then the code examples serve to illustrate the workings of the machinery with specific hackable code.＜/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。 | 4,226円 |
 Programming Puzzles: Python Edition The Guide to Sharpen Your Coding Skills with Engaging and Challenging Puzzles【電子書籍】[ Matthew Whiteside ] 楽天Kobo電子書籍ストア | ＜p＞＜b＞"Programming Puzzles" by Matthew Whiteside offers an engaging collection of challenge and fun puzzles designed to sharpen your problem-solving skills and enhance your programming expertise＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞A diverse range of puzzles to suit different skill levels＜/li＞＜li＞Hints and solutions to facilitate learning and understanding＜/li＞＜li＞Comprehensive explanations that deepen programming knowledge＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞"Programming Puzzles" is a meticulously crafted collection designed to elevate your coding skills through engaging and challenging exercises. The book begins with a helpful guide on getting started, ensuring that readers are well-prepared to tackle the puzzles ahead. As you delve deeper, you'll encounter a series of challenge puzzles that test your logical thinking and problem-solving abilities, followed by fun puzzles that offer a more relaxed yet equally rewarding experience. Hints are provided for the challenge puzzles to guide you through particularly tough spots, ensuring you stay motivated without giving away the solutions. Once you've worked through the puzzles, comprehensive solutions are provided, allowing you to understand different approaches and learn from your mistakes. Each section of the book is designed to progressively build your skills, from basic logic to advanced problem-solving techniques, making it an invaluable resource for anyone looking to improve their programming abilities. The journey through this book is not just about finding solutions; it's about developing a deeper understanding of how to approach and solve complex problems. By the end of this book, you'll have honed your coding skills, enhanced your logical thinking, and gained a new appreciation for the art of problem-solving in programming.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Develop logical thinking and problem-solving skills＜/li＞＜li＞Apply programming concepts to solve challenging puzzles＜/li＞＜li＞Enhance coding proficiency through practical exercises＜/li＞＜li＞Gain insight into different approaches to problem-solving＜/li＞＜li＞Understand the logic behind complex programming solutions＜/li＞＜li＞Improve debugging skills with detailed solution explanations＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞The ideal audience for "Programming Puzzles" includes software developers, data scientists, computer science students, coding bootcamp graduates, and anyone preparing for technical interviews. This book is perfect for individuals looking to enhance their problem-solving and coding skills through a variety of engaging and challenging puzzles. A basic understanding of programming concepts and familiarity with the programming language are recommended prerequisites to fully benefit from the exercises and solutions provided.＜/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。 | 1,033円 |
 Introduction to Logistics Systems Management With Microsoft Excel and Python Examples【電子書籍】[ Gianpaolo Ghiani ] 楽天Kobo電子書籍ストア | ＜p＞INTRODUCTION TO ＜strong＞LOGISTICS SYSTEMS MANAGEMENT＜/strong＞＜/p＞ ＜p＞＜strong＞The updated new edition of the award-winning introductory textbook on logistics system management＜/strong＞＜/p＞ ＜p＞＜em＞Introduction to Logistics Systems Management＜/em＞ provides an in-depth introduction to the methodological aspects of planning, organization, and control of logistics for organizations in the private, public and non-profit sectors. Based on the authors’ extensive teaching, research, and industrial consulting experience, this classic textbook is used in universities worldwide to teach students the use of quantitative methods for solving complex logistics problems.＜/p＞ ＜p＞Fully updated and revised, the third edition places increased emphasis on the complexity and flexibility required by modern logistics systems. In this context, the extensive use of data, descriptive analytics, predictive models, and optimization techniques will be invaluable to support the decisions and actions of logistics and supply chain managers. Throughout the book, brand-new case studies and numerical examples illustrate how various methods can be used in industrial and service logistics to reduce costs and improve service levels. The book:＜/p＞ ＜ul＞ ＜li＞includes new models and techniques that have emerged over the past decade;＜/li＞ ＜li＞describes methodologies for logistics decision making, forecasting, logistics system design, procurement, warehouse management, and freight transportation management;＜/li＞ ＜li＞includes end-of-chapter exercises, Microsoft? Excel? files and Python? computer codes for each algorithm covered;＜/li＞ ＜li＞includes access to a companion website with additional exercises, links to video tutorials, and supplementary teaching material.＜/li＞ ＜/ul＞ ＜p＞To facilitate creation of course material, additional LaTeX source data containing the formulae, optimization models, tables and algorithms described in the book is available to instructors.＜/p＞ ＜p＞＜em＞Introduction to Logistics Systems Management, Third Edition＜/em＞ remains an essential textbook for senior undergraduate and graduate students in engineering, computer science, and management science courses. It is also a highly useful reference for academic researchers and industry practitioners alike.＜/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。 | 9,268円 |
 Programming with MicroPython Embedded Programming with Microcontrollers and Python【電子書籍】[ Nicholas H. Tollervey ] 楽天Kobo電子書籍ストア | ＜p＞It’s an exciting time to get involved with MicroPython, the re-implementation of Python 3 for microcontrollers and embedded systems. This practical guide delivers the knowledge you need to roll up your sleeves and create exceptional embedded projects with this lean and efficient programming language. If you’re familiar with Python as a programmer, educator, or maker, you’re ready to learnーand have fun along the way.＜/p＞ ＜p＞Author Nicholas Tollervey takes you on a journey from first steps to advanced projects. You’ll explore the types of devices that run MicroPython, and examine how the language uses and interacts with hardware to process input, connect to the outside world, communicate wirelessly, make sounds and music, and drive robotics projects.＜/p＞ ＜ul＞ ＜li＞Work with MicroPython on four typical devices: PyBoard, the micro:bit, Adafruit’s Circuit Playground Express, and ESP8266/ESP32 boards＜/li＞ ＜li＞Explore a framework that helps you generate, evaluate, and evolve embedded projects that solve real problems＜/li＞ ＜li＞Dive into practical MicroPython examples: visual feedback, input and sensing, GPIO, networking, sound and music, and robotics＜/li＞ ＜li＞Learn how idiomatic MicroPython helps you express a lot with the minimum of resources＜/li＞ ＜li＞Take the next step by getting involved with the Python community＜/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。 | 2,350円 |
 Python Ethical Hacking from Scratch Think like an ethical hacker, avoid detection, and successfully develop, deploy, detect, and avoid malware【電子書籍】[ Fahad Ali Sarwar ] 楽天Kobo電子書籍ストア | ＜p＞Explore the world of practical ethical hacking by developing custom network scanning and remote access tools that will help you test the system security of your organization Key Features ? Get hands-on with ethical hacking and learn to think like a real-life hacker ? Build practical ethical hacking tools from scratch with the help of real-world examples ? Leverage Python 3 to develop malware and modify its complexities Book Description Penetration testing enables you to evaluate the security or strength of a computer system, network, or web application that an attacker can exploit. With this book, you'll understand why Python is one of the fastest-growing programming languages for penetration testing. You'll find out how to harness the power of Python and pentesting to enhance your system security. Developers working with Python will be able to put their knowledge and experience to work with this practical guide. Complete with step-by-step explanations of essential concepts and practical examples, this book takes a hands-on approach to help you build your own pentesting tools for testing the security level of systems and networks. You'll learn how to develop your own ethical hacking tools using Python and explore hacking techniques to exploit vulnerabilities in networks and systems. Finally, you'll be able to get remote access to target systems and networks using the tools you develop and modify as per your own requirements. By the end of this ethical hacking book, you'll have developed the skills needed for building cybersecurity tools and learned how to secure your systems by thinking like a hacker. What you will learn ? Understand the core concepts of ethical hacking ? Develop custom hacking tools from scratch to be used for ethical hacking purposes ? Discover ways to test the cybersecurity of an organization by bypassing protection schemes ? Develop attack vectors used in real cybersecurity tests ? Test the system security of an organization or subject by identifying and exploiting its weaknesses ? Gain and maintain remote access to target systems ? Find ways to stay undetected on target systems and local networks Who this book is for If you want to learn ethical hacking by developing your own tools instead of just using the prebuilt tools, this book is for you. A solid understanding of fundamental Python concepts is expected. Some complex Python concepts are explained in the book, but the goal is to teach ethical hacking, not Python.＜/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。 | 3,405円 |
 Building Machine Learning Systems with Python Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow, 3rd Edition【電子書籍】[ Luis Pedro Coelho ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞Get more from your data by creating practical machine learning systems with Python＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Develop your own Python-based machine learning system＜/li＞ ＜li＞Discover how Python offers multiple algorithms for modern machine learning systems＜/li＞ ＜li＞Explore key Python machine learning libraries to implement in your projects＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems.＜/p＞ ＜p＞Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you’ll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems.＜/p＞ ＜p＞By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks.＜/p＞ ＜h4＞What you will learn＜/h4＞ ＜ul＞ ＜li＞Build a classification system that can be applied to text, images, and sound＜/li＞ ＜li＞Employ Amazon Web Services (AWS) to run analysis on the cloud＜/li＞ ＜li＞Solve problems related to regression using scikit-learn and TensorFlow＜/li＞ ＜li＞Recommend products to users based on their past purchases＜/li＞ ＜li＞Understand different ways to apply deep neural networks on structured data＜/li＞ ＜li＞Address recent developments in the field of computer vision and reinforcement learning＜/li＞ ＜/ul＞ ＜h4＞Who this book is for＜/h4＞ ＜p＞Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python programming 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。 | 3,631円 |
 Three to See the King ‘Pythonesque ... Quirky, deadpan and quietly unhinged'【電子書籍】[ Magnus Mills ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞'Mills's comedy shares its anthropological glee with The League of Gentlemen...This shouldn't be a speedy page-turner, but it is; light reading with real depth'＜/strong＞ ＜em＞Guardian＜/em＞＜/p＞ ＜p＞＜strong＞'Pythonesque ... Quirky, deadpan and quietly unhinged'＜/strong＞ ＜em＞Scotsman＜/em＞＜/p＞ ＜p＞Living on a windy plain in a house made entirely from tin, a recluse's quiet life is transformed by the severely critical Mary Petrie who arrives unannounced with a trunk of her belongings in tow.＜/p＞ ＜p＞As a procession of new houseguests begins, our narrator is put under pressure as his previously-isolated existence is turned on its head and he is forced to choose between a solitary life and joining the mass exodus of his neighbours...＜/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。 | 1,009円 |
 Python Institute Complete Step By Step Guide For Beginners And Experts: Essential Tutorial For Passing The Python Exams. Real Practice Test With Detailed Screenshots, Answers And Explanations【電子書籍】[ David Mayer ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞Master Python & Become Python Certified to Get Promoted & Start a Whole New Career!＜/strong＞＜/p＞ ＜ul＞ ＜li＞Do you want to demonstrate your proficiency and skill through Python certifications?＜/li＞ ＜li＞Do you want to get prepared for Python certifications exam?＜/li＞ ＜/ul＞ ＜p＞If you answered "yes" to any of these, then this is the perfect educational and informational book for you!＜br /＞ ＜strong＞Hello! Welcome to the "Python Institute Exams Study Guide."＜/strong＞＜br /＞ Getting certified as a Python developer is one of the best achievement you can achieve to enter the job market as a developer! Python is ranked as the second most in-demand programming language in the world. It can be applied in web applications, machine learning, self-driving cars, data science, automation, and much more!＜br /＞ ＜strong＞This book is not only good for the preparation of test but also helpful for all students who want to test their knowledge of python programming language.＜/strong＞＜br /＞ This guide will cover all aspects of the Python Institute Exam Certifications. The author begins by discussing an intro to the Python Institute Certification exam. He described the solid fundamental information of the concepts and a basic understanding of the certification exam.＜/p＞ ＜p＞Here's what makes this book special:＜/p＞ ＜ul＞ ＜li＞Basics & Fundamentals of Python Exams＜/li＞ ＜li＞＜strong＞CAP-31-02 - CERTIFIED ASSOCIATE IN PYTHON PROGRAMMING: Exam Guide & Sample Practice Test＜/strong＞＜/li＞ ＜li＞Prepare for Python Certifications＜/li＞ ＜li＞＜strong＞100% verified answers and explanations to each question＜/strong＞＜/li＞ ＜li＞Build the skills and confidence to crush the Python exam＜/li＞ ＜li＞＜strong＞By the end of this book you will be prepared to take the Python certification Exams＜/strong＞＜/li＞ ＜li＞Finishing this book will provide you a complete understanding and deep knowledge of all the tools＜/li＞ ＜li＞＜strong＞Much, much more!＜/strong＞＜/li＞ ＜/ul＞ ＜p＞＜em＞Interested?＜/em＞＜/p＞ ＜p＞Then Scroll up, Click on "Buy now with 1-Click", and Get Your Copy Now! Also, you will get 50% discount on the simulator!＜br /＞ To get discount for the simulator, you have to send your purchase receipt to mentioned email address in eBook.＜/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。 | 1,334円 |
 Latest Introduction to Programming Using Python Exam 98-381 Questions and Answers【電子書籍】[ Pass Exam ] 楽天Kobo電子書籍ストア | ＜p＞- Total Questions in the guide: 40 Questions with Answers＜br /＞ - Exam Name: Introduction to Programming Using Python＜br /＞ - Exam Code: 98-381＜br /＞ - This guide contains as many latest practice exam questions and answers as possible to prepare you for your 98-381 exam.＜/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。 | 2,670円 |
 Learn AI with Python Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and Keras (English Edition)【電子書籍】[ Gaurav Leekha ] 楽天Kobo電子書籍ストア | ＜p＞The book ‘Learn AI with Python’ is intended to provide you with a thorough understanding of artificial intelligence as well as the tools necessary to create your intelligent applications.This book introduces you to artificial intelligence and walks you through the process of establishing an AI environment on a variety of platforms. It dives into machine learning models and various predictive modeling techniques, including classification, regression, and clustering. Additionally, it provides hands-on experience with logic programming, ASR, neural networks, and natural language processing through real-world examples and fully functional Python implementation. Finally, the book deals with profound models of learning such as R-CNN and YOLO. Object detection in images is also explained in detail using Convolutional Neural Networks (CNNs), which are also explained.By the end of this book, you will have a firm grasp of machine learning and deep learning techniques, as well as a steered methodology for formulating and solving 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。 | 1,597円 |
 Pretrain Vision and Large Language Models in Python End-to-end techniques for building and deploying foundation models on AWS【電子書籍】[ Emily Webber ] 楽天Kobo電子書籍ストア | ＜p＞＜b＞Master the art of training vision and large language models with conceptual fundaments and industry-expert guidance. Learn about AWS services and design patterns, with relevant coding examples＜/b＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Learn to develop, train, tune, and apply foundation models with optimized end-to-end pipelines＜/li＞＜li＞Explore large-scale distributed training for models and datasets with AWS and SageMaker examples＜/li＞＜li＞Evaluate, deploy, and operationalize your custom models with bias detection and pipeline monitoring＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞Foundation models have forever changed machine learning. From BERT to ChatGPT, CLIP to Stable Diffusion, when billions of parameters are combined with large datasets and hundreds to thousands of GPUs, the result is nothing short of record-breaking. The recommendations, advice, and code samples in this book will help you pretrain and fine-tune your own foundation models from scratch on AWS and Amazon SageMaker, while applying them to hundreds of use cases across your organization. With advice from seasoned AWS and machine learning expert Emily Webber, this book helps you learn everything you need to go from project ideation to dataset preparation, training, evaluation, and deployment for large language, vision, and multimodal models. With step-by-step explanations of essential concepts and practical examples, you’ll go from mastering the concept of pretraining to preparing your dataset and model, configuring your environment, training, fine-tuning, evaluating, deploying, and optimizing your foundation models. You will learn how to apply the scaling laws to distributing your model and dataset over multiple GPUs, remove bias, achieve high throughput, and build deployment pipelines. By the end of this book, you’ll be well equipped to embark on your own project to pretrain and fine-tune the foundation models of the future.＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Find the right use cases and datasets for pretraining and fine-tuning＜/li＞＜li＞Prepare for large-scale training with custom accelerators and GPUs＜/li＞＜li＞Configure environments on AWS and SageMaker to maximize performance＜/li＞＜li＞Select hyperparameters based on your model and constraints＜/li＞＜li＞Distribute your model and dataset using many types of parallelism＜/li＞＜li＞Avoid pitfalls with job restarts, intermittent health checks, and more＜/li＞＜li＞Evaluate your model with quantitative and qualitative insights＜/li＞＜li＞Deploy your models with runtime improvements and monitoring pipelines＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞If you’re a machine learning researcher or enthusiast who wants to start a foundation modelling project, this book is for you. Applied scientists, data scientists, machine learning engineers, solution architects, product managers, and students will all benefit from this book. Intermediate Python is a must, along with introductory concepts of cloud computing. A strong understanding of deep learning fundamentals is needed, while advanced topics will be explained. The content covers advanced machine learning and cloud techniques, explaining them in an actionable, easy-to-understand way.＜/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 |
 Data Augmentation with Python Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data【電子書籍】[ Duc Haba ] 楽天Kobo電子書籍ストア | ＜p＞＜b＞Boost your AI and generative AI accuracy using real-world datasets with over 150 functional object-oriented methods and open source libraries Purchase of the print or Kindle book includes a free PDF eBook＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Explore beautiful, customized charts and infographics in full color＜/li＞＜li＞Work with fully functional OO code using open source libraries in the Python Notebook for each chapter＜/li＞＜li＞Unleash the potential of real-world datasets with practical data augmentation techniques＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Data is paramount in AI projects, especially for deep learning and generative AI, as forecasting accuracy relies on input datasets being robust. Acquiring additional data through traditional methods can be challenging, expensive, and impractical, and data augmentation offers an economical option to extend the dataset. The book teaches you over 20 geometric, photometric, and random erasing augmentation methods using seven real-world datasets for image classification and segmentation. You’ll also review eight image augmentation open source libraries, write object-oriented programming (OOP) wrapper functions in Python Notebooks, view color image augmentation effects, analyze safe levels and biases, as well as explore fun facts and take on fun challenges. As you advance, you’ll discover over 20 character and word techniques for text augmentation using two real-world datasets and excerpts from four classic books. The chapter on advanced text augmentation uses machine learning to extend the text dataset, such as Transformer, Word2vec, BERT, GPT-2, and others. While chapters on audio and tabular data have real-world data, open source libraries, amazing custom plots, and Python Notebook, along with fun facts and challenges. By the end of this book, you will be proficient in image, text, audio, and tabular data augmentation techniques.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Write OOP Python code for image, text, audio, and tabular data＜/li＞＜li＞Access over 150,000 real-world datasets from the Kaggle website＜/li＞＜li＞Analyze biases and safe parameters for each augmentation method＜/li＞＜li＞Visualize data using standard and exotic plots in color＜/li＞＜li＞Discover 32 advanced open source augmentation libraries＜/li＞＜li＞Explore machine learning models, such as BERT and Transformer＜/li＞＜li＞Meet Pluto, an imaginary digital coding companion＜/li＞＜li＞Extend your learning with fun facts and fun challenges＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is for data scientists and students interested in the AI discipline. Advanced AI or deep learning skills are not required; however, knowledge of Python programming and familiarity with Jupyter Notebooks are essential to understanding the topics covered 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。 | 3,874円 |
 A Journey to Core Python Experience the Applications of Tuples, Dictionary, Lists, Operators, Loops, Indexing, Slicing, and Matrices【電子書籍】[ Mr. Girish Kumar ] 楽天Kobo電子書籍ストア | ＜p＞The book offers to teach a novice programmer the fundamentals of Python programming from the ground up. The book provides a brief history of Python, followed by exploring Python's fundamental concepts, features, and applications in detail.The book explains Python identifiers, keywords, variables, and assignments, as well as basic operators and decision-making statements. This book covers repetitive code, strings and integers (dictionaries), functions and modules (files), exception handling, and object-oriented programming in all of its variants. The book explains concepts with illustrations, thus making it simple for even the most unskilled reader to grasp the basics of the code execution flow.By the end of this book, you will have a firm grasp of all of Python's programming ideas. Additionally, it will help you to prepare for any upcoming job interviews with your comprehensive Python understanding.＜/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。 | 1,597円 |
 【土日限定1000円OFFクーポン配布中！】 KHAITE カイト パンプス F3050803121 レディース PYTHON EFFETCH LEATHER PERTH T-STRAP SANDALS 10CM 【関税・送料無料】【ラッピング無料】 dk BRANDSHOP・クラージュ楽天市場店 | 127,200円 | |
 【土日限定1000円OFFクーポン配布中！】 FRANCESCO RUSSO フランチェスコ ルッソ パンプス R1S924N216302 レディース PYTHON EFFECT LEATHER THONG ANKLE-STRAP SANDALS HEEL 9CM 【関税・送料無料】【ラッピング無料】 dk BRANDSHOP・クラージュ楽天市場店 | 87,000円 | |
 【土日限定1000円OFFクーポン配布中！】 FRANCESCO RUSSO フランチェスコ ルッソ パンプス R1S919N216302 レディース PYTHON EFFECT LEATHER SANDALS WITH STILETTO HEEL 11CM 【関税・送料無料】【ラッピング無料】 dk BRANDSHOP・クラージュ楽天市場店 | 106,700円 | |
 Hands-On Web Scraping with Python Extract quality data from the web using effective Python techniques【電子書籍】[ Anish Chapagain ] 楽天Kobo電子書籍ストア | ＜p＞＜b＞Work through practical examples to unlock the full potential of web scraping with Python and gain valuable insights from high-quality data＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Build an initial portfolio of web scraping projects with detailed explanations＜/li＞＜li＞Grasp Python programming fundamentals related to web scraping and data extraction＜/li＞＜li＞Acquire skills to code web scrapers, store data in desired formats, and employ the data professionally＜/li＞＜li＞Purchase of the print or Kindle book includes a free PDF eBook＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Web scraping is a powerful tool for extracting data from the web, but it can be daunting for those without a technical background. Designed for novices, this book will help you grasp the fundamentals of web scraping and Python programming, even if you have no prior experience. Adopting a practical, hands-on approach, this updated edition of Hands-On Web Scraping with Python uses real-world examples and exercises to explain key concepts. Starting with an introduction to web scraping fundamentals and Python programming, you’ll cover a range of scraping techniques, including requests, lxml, pyquery, Scrapy, and Beautiful Soup. You’ll also get to grips with advanced topics such as secure web handling, web APIs, Selenium for web scraping, PDF extraction, regex, data analysis, EDA reports, visualization, and machine learning. This book emphasizes the importance of learning by doing. Each chapter integrates examples that demonstrate practical techniques and related skills. By the end of this book, you’ll be equipped with the skills to extract data from websites, a solid understanding of web scraping and Python programming, and the confidence to use these skills in your projects for analysis, visualization, and information discovery.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Master web scraping techniques to extract data from real-world websites＜/li＞＜li＞Implement popular web scraping libraries such as requests, lxml, Scrapy, and pyquery＜/li＞＜li＞Develop advanced skills in web scraping, APIs, PDF extraction, regex, and machine learning＜/li＞＜li＞Analyze and visualize data with Pandas and Plotly＜/li＞＜li＞Develop a practical portfolio to demonstrate your web scraping skills＜/li＞＜li＞Understand best practices and ethical concerns in web scraping and data extraction＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is for beginners who want to learn web scraping and data extraction using Python. No prior programming knowledge is required, but a basic understanding of web-related concepts such as websites, browsers, and HTML is assumed. If you enjoy learning by doing and want to build a portfolio of web scraping projects and delve into data-related studies and application, then this book is tailored for your needs.＜/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。 | 3,874円 |
 洋書 Paperback, Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem Glomarket | *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個人輸入」としての取り扱いになり、すべてニュージャージからお客様のもとへ直送されます。 ・ご注文後、30営業日以内(通常2~3週間)に配送手続きをいたします。配送作業完了後、2週間程度でのお届けとなります。 ・まれに商品入荷状況や国際情勢、運送、通関事情により、お届けが2ヶ月までかかる場合がありますのでお急ぎの場合は注文をお控えください。 ・個人輸入される商品は、すべてご注文者自身の「個人使用・個人消費」が前提となりますので、ご注文された商品を第三者へ譲渡・転売することは法律で禁止されております。 ・関税・消費税が課税される場合があります。詳細はこちらをご確認下さい。PC販売説明文 | 8,591円 |
 Handbook of Python Easy to Carry Python Basics【電子書籍】[ Ramprakash S. ] 楽天Kobo電子書籍ストア | ＜p＞This book depicts the basics of python which is very useful for beginners and those who are all willing to learn and coding in python. Nowadays python plays a major role in the industrial and programming environment, and most industries need python programmers to develop many applications like web development, mobile app development, etc., This book definitely helps for the age group of 10 to anyone., Easy examples are given in each and every chapter that is very easy to understand for user needs.＜/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。 | 326円 |
 Hands-On GPU Computing with Python Explore the capabilities of GPUs for solving high performance computational problems【電子書籍】[ Avimanyu Bandyopadhyay ] 楽天Kobo電子書籍ストア | ＜p＞＜strong＞Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Understand effective synchronization strategies for faster processing using GPUs＜/li＞ ＜li＞Write parallel processing scripts with PyCuda and PyOpenCL＜/li＞ ＜li＞Learn to use the CUDA libraries like CuDNN for deep learning on GPUs＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing.＜/p＞ ＜p＞This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you'll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance.＜/p＞ ＜p＞By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly.＜/p＞ ＜h4＞What you will learn＜/h4＞ ＜ul＞ ＜li＞Utilize Python libraries and frameworks for GPU acceleration＜/li＞ ＜li＞Set up a GPU-enabled programmable machine learning environment on your system with Anaconda＜/li＞ ＜li＞Deploy your machine learning system on cloud containers with illustrated examples＜/li＞ ＜li＞Explore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm.＜/li＞ ＜li＞Perform data mining tasks with machine learning models on GPUs＜/li＞ ＜li＞Extend your knowledge of GPU computing in scientific applications＜/li＞ ＜/ul＞ ＜h4＞Who this book is for＜/h4＞ ＜p＞Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is 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。 | 3,290円 |