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

Google Cloud Platform (GCP)

Having looked at the services provided by Microsoft Azure, let's move on to discussing another alternative cloud platform: GCP. First, we'll talk about GCP's AI Hub service.

AI Hub

One of the available services in the Google Cloud Platform is AI Hub. AI Hub is a fully managed repository of plug-and-play AI components that enable the creation of end-to-end machine learning pipelines. AI Hub provides a wide variety of out-of-the-box machine learning algorithms. AI Hub provides enterprise-grade collaboration capabilities that let companies privately host their machine learning workflows and foster reuse and sharing. You can also easily deploy your models into production on the Google Cloud as well as other environments and cloud providers. AI Hub was released in 2018 so it is in its early stages. Given the importance that Google has assigned to AI research, we expect AI Hub to quickly mature and continue to provide more features...