Deitel Developer Series - Deitel P., Deitel H. - Python for Programmers [2019, PDF, ENG]

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Python for Programmers

Внимание! Раздача обновлена 16 апреля 2020 г. - выложен файл компьютерного качества

Год издания: 2019
Автор: Deitel P., Deitel H.

Издательство: Pearson
ISBN: 978-0135224335
Серия: Deitel Developer Series
Язык: Английский

Формат: PDF
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Нет
Количество страниц: 641

Описание: The professional programmer’s Deitel guide to Pythonwith introductory artificial intelligence case studies

Written for programmers with a background in another high-level language, this book uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details.

In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1—5 and a few key parts of Chapters 6—7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11—16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter for sentiment analysis, cognitive computing with IBM Watson™, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop, Spark™ and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google Translate™, IBM Watson, Microsoft Azure, OpenMapQuest, PubNub and more.

Features
- 500+ hands-on, real-world, live-code examples from snippets to case studies
- IPython + code in Jupyter Notebooks
- Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code
- Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions
- Procedural, functional-style and object-oriented programming
- Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames
- Static, dynamic and interactive visualizations
- Data experiences with real-world datasets and data sources
- Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression
- AI, big data and cloud data science case studies: NLP, data mining Twitter, IBM Watson™, machine learning, deep learning, computer vision, Hadoop, Spark™, NoSQL, IoT
- Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn, Keras and more.
[spoiler="Примеры страниц"]

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[spoiler="Оглавление:"]
Preface xvii
Before You Begin xxxiii
1 Introduction to Computers and Python 1
2 Introduction to Python Programming 31
3 Control Statements 49
4 Functions 71
5 Sequences: Lists and Tuples 101
6 Dictionaries and Sets 137
7 Array-Oriented Programming with NumPy 159
8 Strings: A Deeper Look 191
9 Files and Exceptions 217
10 Object-Oriented Programming 243
11 Natural Language Processing (NLP) 303
12 Data Mining Twitter 331
13 IBM Watson and Cognitive Computing 373
14 Machine Learning: Classification, Regression and Clustering 397
15 Deep Learning 457
16 Big Data: Hadoop, Spark, NoSQL and IoT 501
Index 573
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