Hands-On Python and PyTorch A Practical Guide to Deep Learning

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Free Download Hands-On Python and PyTorch: A Practical Guide to Deep Learning.
English | 2025 | ASIN: B0DW13F2MY | 286 pages | PDF | 2.77 MB
Hands-On Python and PyTorch: A Practical Guide to Deep Learning

Master Deep Learning with Python and PyTorch
Are you ready to dive into the world of deep learning and AI? Hands-On Python and PyTorch: A Practical Guide to Deep Learning is your step-by-step companion to mastering neural networks, machine learning models, and real-world AI applications with Python and PyTorch.
Why This Book?
Comprehensive & Hands-On - Covers everything from basic PyTorch operations to advanced deep learning techniques.
Real-World Applications - Learn to build image classifiers, NLP models, GANs, and reinforcement learning systems.
AI & Deep Learning Integration - Understand how PyTorch works with TensorFlow, OpenCV, and other AI frameworks.
Optimized for Python - Uses Python 3.x for efficient and scalable implementation.
Beginner to Expert Guide - Suitable for students, developers, data scientists, and AI enthusiasts looking to master PyTorch and deep learning.
What You'll Learn
✔ Setting up PyTorch and Python for deep learning projects
✔ Core PyTorch concepts: Tensors, Autograd, and Modules
✔ Building and training neural networks from scratch
✔ Advanced optimization techniques and model tuning
✔ Real-time applications in computer vision, NLP, and reinforcement learning
✔ Deploying AI models efficiently for production
Who Should Read This Book?
Beginners looking to start with PyTorch and deep learning
Developers & Engineers wanting practical AI applications
Machine Learning Enthusiasts integrating deep learning models
Researchers & Students exploring advanced AI concepts
Why Choose This Book Over Others?
Clear Explanations & Code Examples - Every concept is explained with easy-to-follow Python code.
Project-Based Learning - Learn by building real AI applications.
Updated & Practical - Covers the latest PyTorch updates and real-world deep learning applications.

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