The MaxX Academy
Unlearn and then Learn — Welcome to The Maxx Academy, a channel dedicated to making complex academic concepts easy to understand, smooth to follow, and deeply insightful. Our mission is to help you build a strong foundation in Computer Science & Engineering, especially for competitive exams like GATE, UGC NET, and more.
Join us on a journey where we break down, rebuild, and elevate your understanding — one concept at a time.
L-17: Examples of Regular Expression | Theory of Computation
L-16: Regular Expression Introduction | Theory of Computation
P-1: Practice Set | Theory of Computation
L-15: Conversion of Mealy Machine to Moore Machine l Theory of Computation
L:14: Conversion of Moore to Mealy machine | Theory of Computation
L-13: Problem Solving on Moore and Mealy Machine l Theory of Computation
L-12: Moore and Mealy Machine (Finite Automata with Output) | Theory of computation
A-1: Assignment Q&A | Machine Learning
P-4: Practice Set | Machine Learning
P-3: Practice Set | Machine Learning.
P-2: Practice Set l Machine Learning
P-1: Practice Set l Machine Learning
L-11.2: Practice Problem on Minimization of DFA | Theory of Computation
L-11.1 Minimization of DFA (Equivalence Theorem) | Theory of Computation
L-19: Cross- Validation and Classification Accuracy | Machine Learning
L-18: Bias-Variance Tradeoff | Machine Learning
L-17: Support Vector Machine (SVM) | Machine Learning
L-16: Linear Discriminant Analysis (LDA) | Machine Learning
L-15: Naive Bayes Classifier | Machine Learning
L-10.1: Conversion Of NFA to DFA | Theory of Computation
L-10: Comparison Between NFA, DFA and ε-NFA (Epsilon-NFA) | Theory of Computation
L-9.1: ε-Closure Of State & Conversion of ε-NFA (Epsilon-NFA) To NFA | Theory of Automata
L-14: Naive Bayes Classification | Machine Learning
L-13: Naive Bayes | Machine Learning
L-12: Ridge and Lasso Regression | Machine Learning
L-11: Exponential Family, Likelihood Estimation, Maximum Likelihood Estimation | Machine Learning
L-10: Logistic Regression | Machine Learning
L-9: Multiple Linear Regression | Machine Leaning
L-8: Supervised Learning | Type of Supervised Learning | Simple Linear Regression | Machine Learning
L-7: Classification | Training & Testing Split | Overfitting vs Underfitting | Machine Learning