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Deep Learning
Deep Learning by Goodfellow, Bengio, and Courville is the academic standard for deep learning theory. Linear algebra, probability, and optimization Deep networks, CNNs, and RNNs Attention mechanisms and sequence models...
Hands-On Large Language Models
Hands-On Large Language Models is a practical guide to using and building applications with LLMs. Text classification, generation, and embeddings Semantic search and RAG systems Fine-tuning LLMs with real datasets...
Grokking Deep Learning
Grokking Deep Learning teaches deep learning through a build-from-scratch approach for genuine intuition. Gradient descent and backpropagation CNNs, RNNs, and LSTMs explained simply Build networks without frameworks Ideal for beginners...
Neural Networks from Scratch in Python
Neural Networks from Scratch in Python teaches neural network fundamentals from first principles. Forward and backward propagation Dense layers, activations, and optimizers Building CNN and RNN components Essential for deep...
Deep Learning, Foundations and Concepts
Deep Learning: Foundations and Concepts by Bishop offers thorough deep learning foundations. Probabilistic foundations and neural networks CNNs, transformers, and generative models Diffusion models and normalizing flows For graduate students...
The Hundred-Page Language Models Book
The Hundred-Page Language Models Book delivers a compact overview of language models and LLMs. Transformer architecture and attention Pre-training, fine-tuning, and RLHF Practical LLM applications Perfect for developers and ML...
Understanding Deep Learning
Understanding Deep Learning by Simon Prince is a comprehensive, mathematically rigorous deep learning textbook. Supervised, unsupervised, and generative models CNNs, RNNs, attention, and transformers Diffusion models and large language models...
Inside Deep Learning
Inside Deep Learning provides thorough understanding of deep learning theory and practice. Neural network mathematics and intuition CNNs, RNNs, transformers, and attention PyTorch implementations from scratch For ML practitioners and...
llm engineer's handbook
LLM Engineer's Handbook is a practical guide to building, fine-tuning, and deploying LLM applications in production. LLM architecture and fine-tuning RAG pipelines and vector databases Deployment, monitoring, and evaluation For...