State ディープ Deep [COMPUTERS ＆ SCIENCE]
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| 商品 | 説明 | 価格 |
|---|---|---|
 From Deep Sea to Laboratory 3 From Tait's Work on the Compressibility of Seawater to Equations-of-State for Liquids【電子書籍】[ Frederic Aitken ] 楽天Kobo電子書籍ストア | ＜p＞The scientific expedition of H.M.S. Challenger in the 1870s marks the starting point of physical oceanography. This ship traveled the seas of the globe pursuing a dual objective: to conduct an in-depth study of animal life and to observe the physical properties of ocean waters.＜/p＞ ＜p＞Volume 3 focuses on measurements and modeling of liquid compressibility. Based on the work initiated by the physicist Peter Tait, a detailed presentation of liquid equations-of-state is proposed. The physical interpretation of the parameters of these equations is discussed, leading to a description of the "structure" of liquid media.＜/p＞ ＜p＞From Deep Sea to Laboratory is available in three volumes for curious readers drawn to travel, history and science. Students, researchers and teachers of physics, fluid mechanics and oceanography will find material to deepen their knowledge.＜/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。 | 22,504円 |
 State-of-the-Art Deep Learning Models in TensorFlow Modern Machine Learning in the Google Colab Ecosystem【電子書籍】[ David Paper ] 楽天Kobo電子書籍ストア | ＜p＞Use TensorFlow 2.x in the Google Colab ecosystem to create state-of-the-art deep learning models guided by hands-on examples. The Colab ecosystem provides a free cloud service with easy access to on-demand GPU (and TPU) hardware acceleration for fast execution of the models you learn to build. This book teaches you state-of-the-art deep learning models in an applied manner with the only requirement being an Internet connection. The Colab ecosystem provides everything else that you need, including Python, TensorFlow 2.x, GPU and TPU support, and Jupyter Notebooks.＜/p＞ ＜p＞The book begins with an example-driven approach to building input pipelines that feed all machine learning models. You will learn how to provision a workspace on the Colab ecosystem to enable construction of effective input pipelines in a step-by-step manner. From there, you will progress into data augmentation techniques and TensorFlow datasets to gain a deeper understanding of how to work with complex datasets. You will find coverage of Tensor Processing Units (TPUs) and transfer learning followed by state-of-the-art deep learning models, including autoencoders, generative adversarial networks, fast style transfer, object detection, and reinforcement learning.＜/p＞ ＜p＞Author Dr. Paper provides all the applied math, programming, and concepts you need to master the content. Examples range from relatively simple to very complex when necessary. Examples are carefully explained, concise, accurate, and complete. Care is taken to walk you through each topic through clear examples written in Python that you can try out and experiment with in the Google Colab ecosystem in the comfort of your own home or office.＜/p＞ ＜p＞＜strong＞What You Will Learn＜/strong＞＜/p＞ ＜ul＞ ＜li＞ ＜p＞Take advantage of the built-in support of the Google Colab ecosystem＜/p＞ ＜/li＞ ＜li＞ ＜p＞Work with TensorFlow data sets＜/p＞ ＜/li＞ ＜li＞ ＜p＞Create input pipelines to feed state-of-the-art deep learning models＜/p＞ ＜/li＞ ＜li＞ ＜p＞Create pipelined state-of-the-art deep learning models with clean and reliable Python code＜/p＞ ＜/li＞ ＜li＞ ＜p＞Leverage pre-trained deep learning models to solve complex machine learning tasks＜/p＞ ＜/li＞ ＜li＞ ＜p＞Create a simple environment to teach an intelligent agent to make automated decisions＜/p＞ ＜/li＞ ＜/ul＞ ＜p＞＜strong＞Who This Book Is For＜/strong＞＜/p＞ ＜p＞Readers who want to learn the highly popular TensorFlow deep learning platform, those who wish to master the basics of state-of-the-art deep learning models, and those looking to build competency with a modern cloud service tool such as Google Colab＜/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。 | 9,116円 |
 Harnessing AI for a More Just and Peaceful World: Preventing the Deep State and Global Race War 1A, #1【電子書籍】[ WOLDEMARIAM ] 楽天Kobo電子書籍ストア | ＜p＞Harnessing AI for a More Just and Peaceful World: Preventing the Deep State and Global Race War＜/p＞ ＜p＞CONVERSATIONAL CHAT INFORMATIVE BOOK＜/p＞ ＜p＞The book Harnessing Artificial Intelligence for a More Just and Peaceful World: Preventing the Deep State and Global Race War is a thought-provoking and timely work that explores the potential of AI to address some of the most pressing challenges facing humanity today. The book's authors, Google AI's Bard and Abebe Gebre Woldemariam, argue that AI has the potential to be used to prevent the rise of the deep state, promote cross-cultural understanding, and prevent global race war.＜/p＞ ＜p＞The book is divided into two chapters. The first chapter, Leveraging AI to Counter Misinformation and Extremism, examines how AI can be used to identify and combat misinformation and extremism online. The authors discuss how AI algorithms can be used to analyze vast amounts of data, identify patterns, and understand human behavior to detect and remove harmful content. They also discuss how AI can be used to promote media literacy and critical thinking skills among individuals, making them more resilient to misinformation and manipulation.＜/p＞ ＜p＞The second chapter, Promoting Cross-cultural Understanding and Tolerance through AI, explores how AI can be used to promote cross-cultural understanding and tolerance. The authors discuss how AI-powered tools can foster cross-cultural communication, language translation, and cultural exchange. They also discuss how AI can be used to develop early warning systems and conflict resolution tools to prevent conflicts from escalating.＜/p＞ ＜p＞Throughout the book, the authors emphasize the importance of ethical considerations and responsible AI development. They argue that AI should be developed and used in a way that is transparent, accountable, and aligned with ethical principles. They also call for human oversight and collaboration to ensure that AI interventions are effective and do not cause unintended harm.＜/p＞ ＜p＞Harnessing Artificial Intelligence for a More Just and Peaceful World: Preventing the Deep State and Global Race War is an important and timely book that offers a valuable contribution to the debate about the future of AI. The book's authors make a compelling case for the potential of AI to address some of the most pressing challenges facing humanity today, and they provide a number of practical recommendations for ensuring that AI is developed and used in a responsible way. I highly recommend this book to anyone who is interested in the future of AI and its potential to make the world a better place.＜/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。 | 2,450円 |
 State of the Art in Deep Geothermal Energy in Europe With Focus on Direct Heating【電子書籍】[ Johanna Fink ] 楽天Kobo電子書籍ストア | ＜p＞Since nearly 50 % of Europe's energy demand is in the heating and cooling sector, it is expected that geothermal energy will play an important role in the transition to a decarbonized energy system. However, deep geothermal energy is currently harvested mainly from areas with very favorable geothermal conditions. As these areas are geographically limited, the use of geothermal energy in less favorable regions is essential for unleashing the full potential of geothermal energy, since they make up the majority of the total geothermal potential in Central Europe.＜/p＞ ＜p＞Motivated by the growing interest in deep geothermal energy among, e.g., energy companies and communities, this text reviews the state of the art in deep geothermal energy with focus on direct heating in geothermally less favorable regions. It provides an overview of technologies used to generate heat from the deep underground and discusses main technical and non-technical risks associated with deep geothermal projects.＜/p＞ ＜p＞The text addresses readers with an interest in geothermal energy but does not require a background in geoscience or engineering sciences. It is suitable as textbook for Geothermal Energy courses for undergraduate students from different disciplines.＜/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。 | 6,076円 |
 洋書 Utah State University Press Paperback, Secrets of the Greatest Snow on Earth: Weather, Climate Change, and Finding Deep Powder in Utah's Wasatch Mountains and around the World 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 | 6,474円 |
 THE APPLIED DATA SCIENCE WORKSHOP: PROSTATE CANCER CLASSIFICATION AND RECOGNITION USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI【電子書籍】[ Vivian Siahaan ] 楽天Kobo電子書籍ストア | ＜p＞The Applied Data Science Workshop on Prostate Cancer Classification and Recognition using Machine Learning and Deep Learning with Python GUI involved several steps and components. The project aimed to analyze prostate cancer data, explore the features, develop machine learning models, and create a graphical user interface (GUI) using PyQt5.＜/p＞ ＜p＞The project began with data exploration, where the prostate cancer dataset was examined to understand its structure and content. Various statistical techniques were employed to gain insights into the data, such as checking the dimensions, identifying missing values, and examining the distribution of the target variable.＜/p＞ ＜p＞The next step involved exploring the distribution of features in the dataset. Visualizations were created to analyze the characteristics and relationships between different features. Histograms, scatter plots, and correlation matrices were used to uncover patterns and identify potential variables that may contribute to the classification of prostate cancer.＜/p＞ ＜p＞Machine learning models were then developed to classify prostate cancer based on the available features. Several algorithms, including Logistic Regression, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Naive Bayes, Adaboost, Extreme Gradient Boosting, Light Gradient Boosting, and Multi-Layer Perceptron (MLP), were implemented. Each model was trained and evaluated using appropriate techniques such as cross-validation and grid search for hyperparameter tuning.＜/p＞ ＜p＞The performance of each machine learning model was assessed using evaluation metrics such as accuracy, precision, recall, and F1-score. These metrics provided insights into the effectiveness of the models in accurately classifying prostate cancer cases. Model comparison and selection were based on their performance and the specific requirements of the project.＜/p＞ ＜p＞In addition to the machine learning models, a deep learning model based on an Artificial Neural Network (ANN) was implemented. The ANN architecture consisted of multiple layers, including input, hidden, and output layers. The ANN model was trained using the dataset, and its performance was evaluated using accuracy and loss metrics.＜/p＞ ＜p＞To provide a user-friendly interface for the project, a GUI was designed using PyQt, a Python library for creating desktop applications. The GUI allowed users to interact with the machine learning models and perform tasks such as selecting the prediction method, loading data, training models, and displaying results.＜br /＞ The GUI included various graphical components such as buttons, combo boxes, input fields, and plot windows. These components were designed to facilitate data loading, model training, and result visualization. Users could choose the prediction method, view accuracy scores, classification reports, and confusion matrices, and explore the predicted values compared to the actual values.＜/p＞ ＜p＞The GUI also incorporated interactive features such as real-time updates of prediction results based on user selections and dynamic plot generation for visualizing model performance. Users could switch between different prediction methods, observe changes in accuracy, and examine the history of training loss and accuracy through plotted graphs.＜/p＞ ＜p＞Data preprocessing techniques, such as standardization and normalization, were applied to ensure the consistency and reliability of the machine learning and deep learning models. The dataset was divided into training and testing sets to assess model performance on unseen data and detect overfitting or underfitting.＜/p＞ ＜p＞Model persistence was implemented to save the trained machine learning and deep learning models to disk, allowing for easy retrieval and future use. The saved models could be loaded and utilized within the GUI for prediction tasks without the need for retraining.＜/p＞ ＜p＞Overall, the Applied Data Science Workshop on Prostate Cancer Classification and Recognition provided a comprehensive framework for analyzing prostate cancer data, developing machine learning and deep learning models, and creating an interactive GUI. The project aimed to assist in the accurate classification and recognition of prostate cancer cases, facilitating informed decision-making and potentially contributing to improved patient outcomes＜/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。 | 1,933円 |
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洋書 University Press of Colorado Paperback, Deep Freeze: The United States, the International Geophysical Year, and the Origins of Antarctica's Age of Science 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 | 5,347円 |