Deep Learning: A Complete Guide to Neural Networks, Computer Vision, NLP and Modern AI

By Dhiraj Kumar

Deep Learning is one of the most important technologies behind modern artificial intelligence.

But learning deep learning requires more than memorizing neural network architectures. You need to understand how models learn, why they fail, how to improve them, and how to turn trained models into real-world AI systems.

Deep Learning: A Complete Guide to Neural Networks, Computer Vision, NLP and Modern AI provides a structured journey from the foundations of neural networks to modern production-oriented deep learning systems.

Inside this book, you will learn:

- The foundations of deep learning and neural networks
- The mathematics required to understand model training
- Forward propagation and backpropagation
- Gradient descent and modern optimization techniques
- Regularization and techniques for improving generalization
- Convolutional Neural Networks and computer vision
- Image classification, object detection and segmentation
- Recurrent Neural Networks, LSTM and GRU
- Attention mechanisms and Transformer architectures
- Natural Language Processing with deep learning
- Autoencoders, VAEs, GANs and modern generative models
- Transfer learning and fine-tuning
- Parameter-efficient fine-tuning concepts such as LoRA
- Model deployment and production deep learning systems
- Monitoring, scaling, optimization and responsible AI

The book combines intuition, mathematics, practical examples, Python concepts, architecture explanations, common mistakes, interview questions and revision cheat sheets.

Rather than treating deep learning as a collection of disconnected algorithms, the book builds a continuous mental model:

Data → Neural Networks → Training → Optimization → Representation Learning → Transformers → Generative AI → Deployment

Whether you are a student building your foundations, a Data Scientist expanding into deep learning, an ML Engineer preparing for technical interviews, or an AI Engineer learning how modern models are built and deployed, this book is designed to give you a practical and structured foundation.

By the end, you will understand not only how deep learning models work, but also how the individual concepts connect together to form modern AI systems.

• Format: Paperback
• Language: English
• ISBN: B0HP7WHBYV
• ISBN13: 9798165105029
• Release Date: October 2026
• Publisher: Independently Published
• Length: 678 Pages
• Weight: 1.97 lbs.
• Dimensions: 1.4" x 6.0" x 9.0"