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

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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

Building an Image Search Engine Using CLIP: a Multimodal Approach

In the previous chapter, we focused on Transformer models such as BERT and GPT, leveraging their capabilities for sequence learning tasks. In this chapter, we’ll explore a multimodal model, which seamlessly connects visual and textual data. With its dual encoder architecture, this model learns the relationships between visual and textual concepts, enabling it to excel in tasks involving image and text. We will delve into its architecture, key components, and learning mechanisms, leading to a practical implementation of the model. We will then build a multimodal image search engine with text-to-image and image-to-image capabilities. To top it all off, we will tackle an awesome zero-shot image classification project!

We will cover the following topics in this chapter: