You're reading from Artificial Intelligence with Python Your complete guide to building intelligent apps using Python 3.x

Product type Paperback

Published in Jan 2020

Publisher Packt

ISBN-13 9781839219535

Length 618 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Authors (2):

Prateek Joshi

Alberto Artasanchez

View More author details

Table of Contents (26) Chapters

Preface

1. Introduction to Artificial Intelligence

2. Fundamental Use Cases for Artificial Intelligence FREE CHAPTER

3. Machine Learning Pipelines

4. Feature Selection and Feature Engineering

5. Classification and Regression Using Supervised Learning

6. Predictive Analytics with Ensemble Learning

7. Detecting Patterns with Unsupervised Learning

8. Building Recommender Systems

9. Logic Programming

10. Heuristic Search Techniques

11. Genetic Algorithms and Genetic Programming

12. Artificial Intelligence on the Cloud

13. Building Games with Artificial Intelligence

14. Building a Speech Recognizer

15. Natural Language Processing

16. Chatbots

17. Sequential Data and Time Series Analysis

18. Image Recognition

19. Neural Networks

20. Deep Learning with Convolutional Neural Networks

21. Recurrent Neural Networks and Other Deep Learning Models

22. Creating Intelligent Agents with Reinforcement Learning

23. Artificial Intelligence and Big Data

24. Other Books You May Enjoy

25. Index

Amazon Web Services (AWS)

We'll now focus on the top three cloud providers. As you are probably already aware, cloud providers offer much more than artificial services, starting with barebones compute and storage services, all the way to very sophisticated high-level services. As with everything else in this book, we will specifically drill into the artificial intelligence and machine learning services that cloud providers offer, starting with AWS.

Amazon SageMaker

Amazon SageMaker was launched at Amazon's annual re:Invent conference in Las Vegas, Nevada in 2017. SageMaker is a machine learning platform that enables developers and data scientists to create, train, and deploy machine learning (ML) models in the cloud.

A common tool used by data scientists in their day-to-day work is a Jupyter Notebook. These notebooks are documents that contain a combination of computer code such as Python, rich text elements such as paragraphs, equations, graphs, and URLs. Jupyter...