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

Introducing the CLIP model

We have explored computer vision in Chapter 11, Categorizing Images of Clothing with Convolutional Neural Networks, and NLP in Chapter 12, Making Predictions with Sequences Using Recurrent Neural Networks, and Chapter 13, Advancing Language Understanding and Generation with the Transformer Models. In this chapter, we will delve into a model that bridges the realms of computer vision and NLP, the Contrastive Language–Image Pre-Training (CLIP) model developed by OpenAI. Unlike traditional models that are specialized for either computer vision or natural language processing, CLIP is trained to understand both modalities (image and text) in a unified manner. Hence, CLIP excels at understanding and generating relationships between images and natural language.

A modality in ML/AI is a specific way of representing information. Common modalities include text, images, audio, video, and even sensor data.

Excited to delve into the workings...