Видео ютуба по тегу Themaxxacademy

Айфонизация (Октябрь)
Айфонизация (Октябрь)
L-4.1: Problem Solving on Performance Metric | Confusion Matrix Example-1 | Machine Learning
L-4.1: Problem Solving on Performance Metric | Confusion Matrix Example-1 | Machine Learning
L-7: Classification | Training & Testing Split | Overfitting vs Underfitting | Machine Learning
L-7: Classification | Training & Testing Split | Overfitting vs Underfitting | Machine Learning
L-11: Exponential Family, Likelihood Estimation, Maximum Likelihood Estimation | Machine Learning
L-11: Exponential Family, Likelihood Estimation, Maximum Likelihood Estimation | Machine Learning
L-5: Machine Learning Approaches Overview | Machine Learning
L-5: Machine Learning Approaches Overview | Machine Learning
L-7.1: Practice Problem on DFA (Deterministic Finite Automata) | Theory of Automata
L-7.1: Practice Problem on DFA (Deterministic Finite Automata) | Theory of Automata
L-4.2: Problem Solving on Performance Metric | Confusion Matrix Example-2 | Machine Learning
L-4.2: Problem Solving on Performance Metric | Confusion Matrix Example-2 | Machine Learning
L-9.1: ε-Closure Of State & Conversion of ε-NFA (Epsilon-NFA) To NFA | Theory of Automata
L-9.1: ε-Closure Of State & Conversion of ε-NFA (Epsilon-NFA) To NFA | Theory of Automata
L-13: Naive Bayes | Machine Learning
L-13: Naive Bayes | Machine Learning
L-9: Multiple Linear Regression | Machine Leaning
L-9: Multiple Linear Regression | Machine Leaning
L11 & 12: Windowing & Clipping | Cohen-Sutherland Line Clipping Algorithm Explained
L11 & 12: Windowing & Clipping | Cohen-Sutherland Line Clipping Algorithm Explained
L-14: Naive Bayes Classification | Machine Learning
L-14: Naive Bayes Classification | Machine Learning
L-12: Ridge and Lasso Regression | Machine Learning
L-12: Ridge and Lasso Regression | Machine Learning
L-8.2: Problem Solving On NFA (Practice Problems) | Theory of Computation
L-8.2: Problem Solving On NFA (Practice Problems) | Theory of Computation
L-4.3: Loss Function for Regression and Classification | Machine Learning
L-4.3: Loss Function for Regression and Classification | Machine Learning
L-1: Introduction to Theory of Automata and Formal Languages | Theory of Computation
L-1: Introduction to Theory of Automata and Formal Languages | Theory of Computation