Exploremachine-learning

Master the fundamentals of LangChain to build LLM-powered applications. This beginner-friendly course guides you through prompt templates, chains, agents, conversational memory, and document loaders using Python and OpenAI.

Master the visual intuition behind eigenvectors and eigenvalues. Learn how linear transformations stretch space, how to calculate eigenvalues, and why an eigenbasis is crucial for simplifying complex computations in physics, machine learning, and high-dimensional vector databases.

Explore the practical power of matrices and linear algebra. Learn how these mathematical tools drive computer graphics, Google's PageRank algorithm, physics simulations, and modern data science.

Master the inner workings of Large Language Models by coding a complete GPT-style architecture from scratch. Learn tokenization, multi-head attention, pretraining, and supervised fine-tuning using PyTorch and Python. Build, train, and align your own deep learning models.

Master core AWS services, cloud security, architecture, and billing models to ace the AWS Certified Cloud Practitioner (CLF-C02) exam. This comprehensive, structured guide provides foundational cloud knowledge, practical service overviews, and key exam preparation strategies for success.

Master Python programming from scratch. Go from fundamental syntax to building real-world projects in automation, machine learning with scikit-learn, and web development with Django.

Master the inner workings of LLMs by building a GPT-2-style transformer from scratch. Learn neural network fundamentals, GPU optimization, attention mechanisms, pre-training pipelines, instruction tuning, and policy optimization using PyTorch.