introduction to machine learning with python

洋書 Paperback, Introduction to Machine Learning with Python: A Guide for Data ScientistsAI Crash Course A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python【電子書籍】 Hadelin de PontevesMachine Learning on Geographical Data Using Python Introduction into Geodata with Applications and Use Cases【電子書籍】 Joos KorstanjeAn Introduction to Python Programming: A Practical Approach step-by-step approach to Python programming with machine learning fundamental and theoretical principles.【電子書籍】 Dr. Krishna Kumar MohbeyPythonではじめる機械学習 scikit‐learnで学ぶ特徴量エンジニアリングと機械学習の基礎 / 原タイトル:Introduction to Machine Learning with Python 本/雑誌 / AndreasC.Muller/著 SarahGuido/著 中田秀基/訳An Introduction to Python Programming: A Practical Approach: Using Python to Solve Complex Problems with a Burst of Machine Learning (English Edition)【電子書籍】 Dr. Krishna Kumar MohbeyIntroduction to Machine Learning with Python【電子書籍】 Deepti ChopraIntroduction to Machine Learning with Python A Guide for Data Scientists【電子書籍】 Sarah GuidoPython Machine Learning: Introduction to Machine Learning with Python【電子書籍】 Frank MillsteinIntroduction to Machine Learning with Python【電子書籍】 Deepti ChopraIntroduction to Machine Learning in the Cloud with Python Concepts and Practices【電子書籍】 Pramod Gupta
 

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  • *** 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...
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  • <p><strong>Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves.</strong></p> <h4>Key Features</h4> <ul> <li>Learn from friendly, plain English explanations and practical activities</li> <li>Put ideas into action with 5 hands-on projects that show step-by-step how to build intelligent software</li> <li>Use AI to win classic video games and construct a virtual self-driving car</li> </ul> <h4>Book Description</h4> <p>Welcome to the Robot World ... and start building intelligent software now!</p> <p>Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full...
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  • <p>Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data in Python.</p> <p>This book starts with an introduction to geodata and covers topics such as GIS and common tools, standard formats of geographical data, and an overview of Python tools for geodata. Specifics and difficulties one may encounter when using geographical data are discussed: from coordinate systems and map projections to different geodata formats and types such as points, lines, polygons, and rasters. Analytics operations typically applied to geodata are explained such as clipping, intersecting, buffering, merging, dissolving, and erasing, with implementations in Python. Use cases and examples are included. The book also focuses on applying more advanced machine learning approaches to geographical data and presents interpolation, classification, regression, and clustering via examples and use cases.</p> <p>This book is your go...
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  • <p>The book ‘Introduction to Python Programming: A Practical Approach’ lays out a path for readers who want to pursue a career in the field of computer software development. It covers the fundamentals of Python programming as well as machine learning principles. Students will benefit from the examples that are included with each concept, which will aid them in understanding the concept.This book provides a practical understanding of Python programming using numerous programs and examples. It also develops problem-solving and code-writing abilities for the readers. This book covers Python fundamentals, operators, and data structures such as strings, lists, dictionaries, and tuples. It also contains information on file and exception handling. The implementation of a machine learning model has also been included in this book.With the help of this book, students and programmers can improve their programming skills as well as their ability to sprint towards a rewarding career.</p>画...
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  • ご注文前に必ずご確認ください<商品説明>Pythonの機械学習用ライブラリの定番、scikit‐learnのリリースマネージャを務めるなど開発に深く関わる著者が、scikit‐learnを使った機械学習の方法を、ステップバイステップで解説します。ニューラルネットを学ぶ前に習得しておきたい機械学習の基礎をおさえるとともに、優れた機械学習システムを実装し精度の高い予測モデルを構築する上で重要となる「特徴量エンジニアリング」と「モデルの評価と改善」について多くのページを割くなど、従来の機械学習の解説書にはない特長を備えています。<収録内容>1章 はじめに2章 教師あり学習3章 教師なし学習と前処理4章 データの表現と特徴量エンジニアリング5章 モデルの評価と改良6章 アルゴリズムチェーンとパイプライン7章 テキストデータの処理8章 おわりに<商品詳細>商品番号:NEOBK-2097933AndreasC. Muller / Cho SarahGuido / Cho Nakata Hideki / Yaku / Python Dehajimeru Kikai Gakushu Scikit Learn De Manabu Tokucho Ryo Engineering to Kikai Gakushu No Kiso / Original Title: Introduction to Machine Learning with Pythonメディア:本/雑誌重量:653g発売日:...
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  • <p><strong>step-by-step approach to Python programming with machine learning fundamental and theoretical principles.</strong></p> <p>KEY FEATURES</p> <p>● Introduces readers to Python programming in a very simple way.</p> <p>● Extensive practical demonstration of Python concepts using numerous examples.</p> <p>● Implementation of machine learning in Python using hands-on techniques.</p> <p>DESCRIPTION</p> <p>The book 'Introduction to Python Programming: A Practical Approach' lays out a path for readers who want to pursue a career in the field of computer software development. It covers the fundamentals of Python programming as well as machine learning principles. Students will benefit from the examples that are included with each concept, which will aid them in understanding the concept.</p> <p>This book provides a practical understanding of Python programming using numerous programs and examples. It also develops problem-solving and code-writing ab...
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  • <p>Machine learning is a subfield of artificial intelligence, broadly defined as a machine's capability to imitate intelligent human behavior. Like humans, machines become capable of making intelligent decisions by learning from their past experiences. Machine learning is being employed in many applications, including fraud detection and prevention, self-driving cars, recommendation systems, facial recognition technology, and intelligent computing. This book helps beginners learn the art and science of machine learning. It presens real-world examples that leverage the popular Python machine learning ecosystem,</p> <p>The topics covered in this book include machine learning basics: supervised and unsupervised learning, linear regression and logistic regression, Support Vector Machines (SVMs). It also delves into special topics such as neural networks, theory of generalisation, and bias and fairness in machine learning. After reading this book, computer science and engineering s...
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  • <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...
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  • <p>Machine learning is <strong>the science of getting machines and computers to act and learn on their own without being programmed explicitly</strong>. In just the past decade, this field has given us practical speech recognition, self-driving cars, greatly improved understanding of the overall human genome, effective web search and much more. Therefore, there is no wondering why machine learning is so pervasive today.In this book, you will learn more about <strong>interpreting machine learning techniques using Python</strong>. You will also gain practice as you implement the most popular machine learning techniques on some real-world examples and you will learn both about the theoretical and practical machine learning implementation using Python's machine learning libraries.At the end of the book, you will be able to cope with more complex machine learning issues solving your own problems using Python and its libraries specifically crafted for machine learning.</p> <p...
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    商品の説明

  • <p>Machine learning is a subfield of artificial intelligence, broadly defined as a machine's capability to imitate intelligent human behavior. Like humans, machines become capable of making intelligent decisions by learning from their past experiences. Machine learning is being employed in many applications, including fraud detection and prevention, self-driving cars, recommendation systems, facial recognition technology, and intelligent computing. This book helps beginners learn the art and science of machine learning. It presens real-world examples that leverage the popular Python machine learning ecosystem,The topics covered in this book include machine learning basics: supervised and unsupervised learning, linear regression and logistic regression, Support Vector Machines (SVMs). It also delves into special topics such as neural networks, theory of generalisation, and bias and fairness in machine learning. After reading this book, computer science and engineering students - at...
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  • <p>This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.</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。
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