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Python Machine Learning By Example

Python Machine Learning By Example

By : Yuxi (Hayden) Liu
4.9 (9)
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Python Machine Learning By Example

Python Machine Learning By Example

4.9 (9)
By: Yuxi (Hayden) Liu

Overview of this book

The fourth edition of Python Machine Learning By Example is a comprehensive guide for beginners and experienced machine learning practitioners who want to learn more advanced techniques, such as multimodal modeling. Written by experienced machine learning author and ex-Google machine learning engineer Yuxi (Hayden) Liu, this edition emphasizes best practices, providing invaluable insights for machine learning engineers, data scientists, and analysts. Explore advanced techniques, including two new chapters on natural language processing transformers with BERT and GPT, and multimodal computer vision models with PyTorch and Hugging Face. You’ll learn key modeling techniques using practical examples, such as predicting stock prices and creating an image search engine. This hands-on machine learning book navigates through complex challenges, bridging the gap between theoretical understanding and practical application. Elevate your machine learning and deep learning expertise, tackle intricate problems, and unlock the potential of advanced techniques in machine learning with this authoritative guide.
Table of Contents (18 chapters)
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16
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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...

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