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

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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

Microsoft Azure

Having covered AWS, let's take a look at the features of Microsoft's offering within the area of cloud services: Microsoft Azure.

Microsoft Azure Machine Learning Studio

Microsoft Azure Machine Learning Studio is Microsoft's answer to Amazon SageMaker. Machine Learning Studio is a collaborative tool with a simple drag-and-drop interface that allows the user to build, test, and deploy machine learning models. Machine Learning Studio enables model publishing that can be consumed by other applications and can easily integrate with BI tools such as Excel.

Machine Learning Studio interactive workspace – In Chapter 3, Machine Learning Pipelines, we learned about the machine learning pipeline. The Machine Learning Studio interactive workspace simplifies pipeline development by allowing users to easily ingest data into the workspace, transform the data, then analyze that data through various data manipulation and statistical functions, and finally...