THEORY OF COMPUTATION - LECTURE #29- Writing Context Free grammars

Ensemble Methods

Regularization Techniques

Optimization Techniques

Practical Challenges in Neural Network Training- Overfitting, Vanishing & exploding gradients & more

Introduction to Deep Learning

Naive Bayes Classifier With Examples

Decision Tree Algorithm _ Iterative Dichotomiser -3 (ID3) with examples

Logistic Regression Classifier with examples

Back Propagation in Feed Forward Neural Networks

Multi Layer Perceptron (MLP) / Feed Forward Neural Networks

Linear Regression - Part 2: Gradient Descent and Matrix Solutions

Linear Regression-Part 1

Interactive Proof Systems and class IP

Approximation Algorithms for Bin Packing Problem

Approximation Algorithm for Vertex Cover

Approximation Algorithms for Minimum Partitioning

Approximation Algorithm for Travelling Salesman Problem

THEORY OF COMPUTATION- LECTURE #40- Variants of Turing Machines- Non deterministic & Enumerator TMs

THEORY OF COMPUTATION-LECTURE #39-Designing Turing Machine as Transducers

THEORY OF COMPUTATION -LECTURE # 43 - Recursive and Recursively enumerable languages

THEORY OF COMPUTATION-Lecture-#38- Turing Machine as acceptors - Designing Examples

Computation Complexity- Proof that PRIMES is in class CoRP

Computational Complexity- Randomized algorithms&Probabilistic Complexity classes - RP, CoRP, BPP&ZPP

THEORY OF COMPUTATION- Lecture #36- Context Sensitive Grammar (CSG) and Linear Bounded Automata(LBA)