Learn about AI with these books, videos, and tutorials

This collection of AI resources will get you up to speed on the basics, best practices, and latest techniques.

June 6, 2018
Neuron branches Neuron branches (source: Shannon Hauser via Flickr)

Whether you’re just getting into artificial intelligence (AI) or you’re an experienced practitioner, you’ll find something useful on our list of AI resources.

The items on this list were curated by O’Reilly’s editorial experts.

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Introduction to AI

Use these introductory resources to quickly understand the basics of AI.

What is Artificial Intelligence?Mike Loukides and Ben Lorica examine the factors that have made AI a hot topic in recent years.

AI is the New ElectricityAndrew Ng explores best practices for incorporating AI, machine learning, and deep learning into your organization.

Learn from the Experts about AI: Matthew Kirk — Matthew Kirk offers a helpful definition of AI and notes that aspects of AI have already been used by businesses for decades.

The Conversational Enterprise: Use Cases and Best Practices for Chatbots in the EnterpriseSusan Etlinger shares techniques for building consumer-facing chatbots.

Going deeper with AI

These resources cover practical applications of AI tools and techniques.

Hands-On Machine Learning with Scikit-Learn and TensorFlow — Using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—Aurélien Géron outlines the concepts and tools for building intelligent systems.

TensorFlow, Machine Learning, and Learning to Learn — Sherry Moore discusses the latest developments in TensorFlow, the world’s most popular machine learning framework.

Fundamentals of Deep Learning — Nikhil Buduma provides examples and clear explanations to guide you through the major concepts of deep learning.

Deep Learning Models and Computer Vision with TensorFlow — Lucas Adams walks you through the fundamentals of deep learning and TensorFlow with step-by-step guidance.

Getting Started with Deep Learning using Keras and Python — Mike Williams shows you how to experiment with deep learning neural networks using Keras, an alternative to TensorFlow and Theano.

Introduction to Deep Learning Using PyTorch — Alfredo Canziani and Goku Mohandas explore PyTorch, a deep-learning framework in Python.

Advanced AI tools and methods

Refine your AI knowledge with these resources.

Backing Off Toward Simplicity: Understanding the Limits of Deep Learning — Stephen Merity investigates what tasks deep learning excels at, what tasks trigger a failure mode, and where deep learning research is going.

Reinforcement Learning and OpenAI Gym — Justin Francis outlines the core concepts of reinforcement learning and illustrates how OpenAI Gym software incorporates those concepts.

Active Learning and Transfer Learning — Lukas Biewald explores the state of the art in training data, active learning, and transfer learning.

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