AI Projects in PyTorch: Hands-On Projects in Vision, Text, and Generative Models
English | 2026 | ISBN: B0FPLFB58S | 349 pages | PDF | 10.81 MB
Dive into computer vision, natural language processing, and recommender systems by building end-to-end projects in PyTorch - one of the most widely used deep learning frameworks among researchers and engineers worldwide. This book takes you from the fundamentals to complete, hands-on projects, giving you the confidence to start creating your own AI solutions.
The book begins with a chapter on the fundamentals of machine learning, laying the groundwork by introducing key aspects of an ML project such as data preprocessing, feature engineering, model training, and evaluation, along with essential concepts like overfitting and underfitting. The following chapter, "Tensors in PyTorch," explores data handling in PyTorch - from basic tensor operations to advanced gradient computations - providing a deeper understanding of data transformations.
With the foundations in place, the book moves on to hands-on projects. Chapter 3 introduces you to the world of computer vision, where you will build an image classifier using convolutional neural networks. The next three chapters immerse you in natural language processing: beginning with text classification (Chapter 4), tackling a range of NLP tasks with Hugging Face (Chapter 5), and culminating in the creation of a storytelling language model (Chapter 6).
The focus then shifts to other key AI domains - you will tackle an audio classification task (Chapter 7), build a recommender system in PyTorch (Chapter 8), and finish with a multi-modal project that combines computer vision and natural language processing to build an image captioning system (Chapter 9).
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