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O'Reilly Data Show

The O'Reilly Data Show Podcast explores the opportunities and techniques driving big data, data science, and AI. Subscribe on Apple Podcasts, Stitcher, Google Play, and RSS.

Mastering Object-oriented Python

This book will present detailed examples of almost all of the special method names that support creating classes that integrate seamlessly with Python's built-in features. It will show you how to use JSON, YAML, Pickle, CSV, XML, Shelve, and SQL to create persistent objects and transmit objects between processes.

Architects of Intelligence

Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community.

Artificial Intelligence with Python

During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques.

Beginning Data Science with Python and Jupyter

Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world.

Hands-On Deep Learning Architectures with Python

Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures.

Hands-On Reinforcement Learning with Python

The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration.

Python Deep Learning for Beginners

This course will teach you to apply deep learning concepts using Python to solve challenging tasks. You'll build a Python deep learning-based image recognition system and deploy and integrate images into web apps or phone apps.

Python Machine Learning Cookbook - Second Edition

With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach.

Python Machine Learning - Third Edition

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.

Understanding Machine Learning with Python

Use your data to predict future events with the help of machine learning. This course will walk you through creating a machine learning prediction solution and will introduce Python, the scikit-learn library, and the Jupyter Notebook environment.

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