Deep Learning from Scratch

Deep Learning from Scratch: Building with Python from First Principles 1st Edition

Description:
Deep Learning from Scratch: Building with Python from First Principles by Seth Weidman offers a comprehensive introduction to deep learning for data scientists and software engineers. This book takes a first-principles approach to deep learning, guiding you through the creation of neural networks from the ground up. Whether you’re a seasoned professional or just getting started, this book ensures a clear understanding of how neural networks operate mathematically, computationally, and conceptually.

In this hands-on guide, you’ll begin with the fundamentals of deep learning and move quickly into advanced architectures like multilayer neural networks, convolutional neural networks, and recurrent neural networks. What sets this book apart is the detailed explanation of how these models are built from scratch, using easy-to-understand Python frameworks, and then implemented with the popular PyTorch library.

Key Features:

• Understand Neural Networks: Learn how neural networks function through clear mental models, working code examples, and mathematical explanations.
• Implement Networks from Scratch: Master multilayer neural networks with step-by-step implementations using an object-oriented framework.
• Explore Advanced Architectures: Build convolutional and recurrent neural networks from scratch, understanding their core principles.
• Hands-on with PyTorch: Apply your knowledge by building neural networks in PyTorch, a popular deep learning library.

Table of Contents (Short Version)

1. Introduction to Deep Learning
2. Neural Networks from First Principles
3. Implementing Multilayer Neural Networks
4. Convolutional Neural Networks
5. Recurrent Neural Networks
6. Implementing with PyTorch
7. Optimizing Neural Networks
8. Case Studies in Deep Learning

What Is Deep Learning from Scratch?

“Deep Learning from Scratch” refers to building and implementing deep learning models, such as neural networks, entirely from the ground up. Instead of relying on pre-built frameworks or libraries, you write code to construct the individual components of neural networks, such as layers, activation functions, and loss functions. This approach provides a deeper understanding of how neural networks work, offering insights into the mathematical and computational principles that underpin modern AI.

Instant eBook Delivery – Study Anywhere, Anytime

With Deep Learning from Scratch, you can dive into deep learning immediately. Once your payment is processed, you’ll receive a PDF download link, giving you instant access to the book and all its valuable content.

Product Details:

• Publisher: O’Reilly Media; 1st edition (October 15, 2019)
• ISBN-13: 9789352139026
• Language: English
• Print Length: 250 pages
• Format Type: PDF