Machine Learning Tutorials
Master machine learning, data science, and analytics through interactive tutorials and hands-on projects
Neural Networks Fundamentals
Master the foundations of neural networks from mathematical principles to practical implementations. 8 comprehensive chapters covering feedforward networks, backpropagation, activation functions, CNNs, RNNs, and LSTMs.
Complete neural networks course with detailed explanations, formulas, and code examples covering feedforward networks, backpropagation, CNNs, RNNs, and LSTMs.
Transformer Architecture Deep Dive
Master the Transformer architecture that revolutionized NLP. 10 comprehensive chapters covering attention mechanisms, self-attention, multi-head attention, positional encoding, encoder-decoder architecture, and implementation details.
Deep dive into Transformer architecture with extensive formulas, code examples, and visual explanations covering attention, self-attention, multi-head attention, and complete implementation.
Large Language Models (LLMs)
Master Large Language Models from pre-training to fine-tuning. 8 comprehensive chapters covering BERT, GPT, transfer learning, fine-tuning strategies, prompt engineering, and practical applications.
Complete LLM course covering BERT, GPT, pre-training, fine-tuning, LoRA, prompt engineering, and practical applications with detailed explanations and code examples.
RAG & Retrieval Systems
Master Retrieval-Augmented Generation (RAG) systems from vector databases to production deployment. 7 comprehensive chapters covering embeddings, retrieval strategies, RAG architecture, and building production systems.
Complete RAG tutorial covering embeddings, vector databases, retrieval strategies, RAG architecture, and production deployment with detailed explanations and code examples.
Agentic AI & LLM Agents
Master AI Agents and Agentic AI systems. 8 comprehensive chapters covering agent architectures, tool-using agents, ReAct framework, multi-agent systems, agent orchestration, and building production agents.
Complete agentic AI course covering agent architectures, tool-using agents, ReAct, multi-agent systems, orchestration, and production deployment with detailed explanations and code examples.