Foundations
Calculus for Machine Learning
Master derivatives, integrals, gradients, and backpropagation for neural networks.
Read More
Library
Practical learning resources covering AI/ML fundamentals, software development, and computer science concepts. My reference materials for understanding systems from first principles. Available for anyone serious about learning.
Browse TopicsMaster the Math
Foundations
Linear Algebra for Machine Learning
Deep dive into vectors, matrices, eigenvalues, and SVD that power ML systems.
Read More
Foundations
Probability & Statistics for Machine Learning
Comprehensive guide to Bayes theorem, distributions, MLE, and information theory.
Read More
Collection
DBMS
Comprehensive guide to database systems, SQL, normalization, and transactions.
Read More