The Little Book of Deep Learning
François Fleuret
Concise introduction to deep learning covering foundations, model components, architectures (CNNs, Transformers), and applications in image generation, text synthesis, and reinforcement learning.
Loading the book...
Keep reading
-
Next in this topic
Deep Learning in Neural Networks: An OverviewAuthoritative historical survey of deep learning with 888 references. Covers supervised, unsupervised, and reinforcement learning approaches in deep neural networks from their origins to 2014.
Verified PDF · Secure download - Deep Learning Algorithms
Collection of open access research on deep learning methods and applications. Covers CNN architectures, medical imaging, plant disease detection, underwater robotics, and reinforcement learning.
Verified PDF · Secure download - Foundations of Large Language Models
Comprehensive textbook on LLM foundations covering pre-training, generative models, prompting strategies, chain-of-thought reasoning, alignment methods (RLHF), and inference optimization.
Verified PDF · Secure download - Prompt Engineering
Google's official guide to prompt engineering covering LLM configuration, sampling controls, zero-shot and few-shot prompting, chain-of-thought, ReAct, and best practices for working with AI models.
Verified PDF · Secure download - Speech and Language Processing
The gold standard NLP textbook from Stanford and CU Boulder. Covers tokenization, language models, transformers, LLMs, machine translation, speech recognition, and information extraction.
Verified PDF · Secure download