You're reading from Python Machine Learning By Example Unlock machine learning best practices with real-world use cases

Product type Paperback

Published in Jul 2024

Publisher Packt

ISBN-13 9781835085622

Length 518 pages

Edition 4th Edition

Languages

Python

Tools

PyTorch

Concepts

Computer Vision

Author (1):

Yuxi (Hayden) Liu

View More author details

Table of Contents (18) Chapters

Preface

1. Getting Started with Machine Learning and Python

2. Building a Movie Recommendation Engine with Naïve Bayes FREE CHAPTER

3. Predicting Online Ad Click-Through with Tree-Based Algorithms

4. Predicting Online Ad Click-Through with Logistic Regression

5. Predicting Stock Prices with Regression Algorithms

6. Predicting Stock Prices with Artificial Neural Networks

7. Mining the 20 Newsgroups Dataset with Text Analysis Techniques

8. Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling

9. Recognizing Faces with Support Vector Machine

10. Machine Learning Best Practices

11. Categorizing Images of Clothing with Convolutional Neural Networks

12. Making Predictions with Sequences Using Recurrent Neural Networks

13. Advancing Language Understanding and Generation with the Transformer Models

14. Building an Image Search Engine Using CLIP: a Multimodal Approach

15. Making Decisions in Complex Environments with Reinforcement Learning

16. Other Books You May Enjoy

17. Index

Demystifying neural networks

Here comes probably the most frequently mentioned model in the media, Artificial Neural Networks (ANNs); more often, we just call them neural networks. Interestingly, the neural network has been (falsely) considered equivalent to machine learning or artificial intelligence by the general public.

An ANN is just one type of algorithm among many in machine learning, and machine learning is a branch of artificial intelligence. It is one of the ways we achieve Artificial General Intelligence (AGI), which is a hypothetical type of AI that can think, learn, and solve problems like a human.

Regardless, it is one of the most important machine learning models and has been rapidly evolving along with the revolution of Deep Learning (DL).

Let’s first understand how neural networks work.