Oreilly – Python Fundamentals 2019-8

Oreilly – Python Fundamentals 2019-8 Downloadly IRSpace

Aug 16, 2025 - 06:57 Updated: Aug 17, 2025 - 19:33

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Oreilly – Python Fundamentals 2019-8

Python Fundamentals, The professional programmer’s Deitel video guide to Python development with the powerful IPython and Jupyter Notebooks platforms. Python Fundamentals LiveLessons with Paul Deitel is a code-oriented presentation of Python—one of the world’s most popular and fastest growing languages. In the context of scores of real-world code examples ranging from individual snippets to complete scripts, Paul will demonstrate coding with the interactive IPython interpreter and Jupyter Notebooks. You’ll quickly become familiar with the Python language, its popular programming idioms, key Python Standard Library modules and several popular open-source libraries. In the Intro to Data Science videos, Paul lays the groundwork for later lessons in which he’ll introduce some of today’s most compelling, leading-edge computing technologies, including 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, sentiment analysis through deep learning with recurrent neural networks, big data with Hadoop®, Spark™ streaming, NoSQL databases and the Internet of Things.

What you’ll learn

Before You Begin—Configure your system for Python, obtain the code examples, Python package managers, Paul’s contact info
Lesson 1—Test-Drives: Using IPython and Jupyter Notebooks—Work with snippets and scripts in the context of IPython and Jupyter Notebooks
Lesson 2—Intro to Python Programming—Variables, types, operators, strings, I/O, decisions, objects and dynamic typing
Lesson 3—Control Statements—if, if…else, if…elif…else, for, while, break, continue, augmented assignments, boolean operators, intro to lists
Lesson 4—Functions—Custom function definitions, importing libraries, simulation with random-number generation, scope, default parameter values, keyword arguments, arbitrary argument lists, methods, intro to tuples, intro to functional-style programming