Hands-On PyTorch for AI and Machine Learning 2026: A Practical Guide to Building Smart Models, Training Neural Networks, and Deploying Deep Learning Solutions with Python - Softcover

Kessler, Adrian M

Softcover

ISBN 13: 9798253051085

Publisher: Independently published, 2026

Synopsis

Are you a developer, data scientist, or aspiring AI engineer looking to take your skills to the next level with PyTorch? Hands-On PyTorch for AI and Machine Learning 2026 is your ultimate guide to mastering modern deep learning using the most flexible and research-backed framework available today.
This isn’t just another machine learning book—it’s a practical, project-driven blueprint that walks you through every critical step of designing, building, training, and deploying neural networks using Python and PyTorch. Whether you're transitioning from TensorFlow, starting from scratch, or seeking a real-world playbook for AI, this guide is for you.
Inside, you’ll learn how to:

• Understand the fundamentals of AI, machine learning, and deep learning in plain English
• Work with tensors, autograd, and dynamic computation graphs like a pro
• Build your first neural network from scratch using torch.nn and Sequential
• Train models with optimizers like SGD, Adam, and RMSProp, and fine-tune hyperparameters
• Develop powerful CNNs for image classification and apply them to datasets like MNIST and CIFAR-10
• Dive into natural language processing with RNNs, GRUs, LSTMs, and Transformer architectures
• Use pretrained models from torchvision.models and Hugging Face for transfer learning
• Create custom datasets, implement data loaders, and write robust preprocessing pipelines
• Evaluate your models with precision, recall, F1-score, and visualize performance using TensorBoard or Weights & Biases
• Deploy models using Flask, FastAPI, or ONNX—and integrate them into mobile or web apps
• Leverage PyTorch Lightning to write cleaner, scalable, and production-ready code
• Stay ahead of the curve with future trends like AutoML, edge AI, quantization, and responsible AI practices

What sets this book apart:

• Future-focused for 2026 and beyond—updated tools, trends, and deployment practices
• Code-first, no-fluff approach with real projects and clean architecture
• Written for clarity—ideal for developers, ML engineers, and anyone transitioning into AI
• Includes practical exercises and deployable templates for career-ready skills
• Applicable across industries: healthcare, finance, cybersecurity, robotics, and more

Whether you're building a career in AI, optimizing your production pipelines, or simply want to stay relevant in the era of intelligent software, this book is your hands-on companion.
Perfect for learners at any level ready to build deep learning models that actually work.

Edition details

• Publisher: Independently published
• Publication date: 2026
• Language: English
• ISBN 13: 9798253051085
• Binding: Paperback
• Number of pages: 203