29) Matrix multiplication from scratch in Python No NumPy, no libraries Coding for ML [Lecture 29]5просмотровмесяц назад
27) Regularization in ML explained simply Lasso (L1) and Ridge (L2) Foundations for ML [Lecture 27]7просмотровмесяц назад
26) Adam Optimizer from scratch Gradient descent made better Foundations for ML [Lecture 26]2просмотрамесяц назад
25) RMSprop Gradient Descent from scratch Optimization in ML Foundations for ML [Lecture 25]12просмотровмесяц назад
24) Momentum-based gradient descent from scratch optimization Foundations for ML [Lecture 24]8просмотровмесяц назад
23) Stochastic Gradient Descent from scratch Intro to Optimization Foundations for ML [Lecture 23]6просмотровмесяц назад
20) Partial Derivatives and Gradient Descent The Engine Driving ML ML foundations [Lecture 20]3просмотрамесяц назад
19) Integral calculus for Machine Learning Mathematical foundations for ML [Lecture 19]1просмотрмесяц назад
18) Chain rule for Machine Learning Calculus for ML Mathematical Foundations for ML [Lecture 18]3просмотрамесяц назад
17) Introduction to Calculus for Machine Learning Foundations for ML [Lecture 17]5просмотровмесяц назад
16) Foundations for ML Naive-Bayes classification, ML model evaluation confusion matrix [Lecture 16]1просмотрмесяц назад
15) Foundations for Machine Learning Null & Alternate hypothesis in probability [Lecture 15]2просмотрамесяц назад
13) Foundations for Machine Learning Bayes Theorem - Intuition and basics [Lecture 13]4просмотрамесяц назад
12) Foundations for Machine Learning Conditional probability Probability & Statistics [Lecture 12]3просмотрамесяц назад
