ML - Lecture 12.2 Unsupervised Learning | Dimensionality Reduction | PCA

ML - Lecture 12.1 Unsupervised Learning | Clustering

ML - Lecture 11 Recurrent Neural Networks RNN | LSTM

ML - Lecture 10 Convolutional Neural Networks CNN

DS - Shell Sort and External Sort

Lecture 9.2 Neural Networks - Back propagation

ML - Lecture 9.1 Neural Networks Intro

DS - Sorting - Merge sort

DS - Heaps part 2

ML - Lecture 8 - Ensemble Learning || XGBoost, Random Forest and Stacking

DS - Hashing

Splay Tree and B-Tree

ML - Lecture 7 - Ensemble Learning I

ML - Lecture 6.2 - Hyperparameters Tuning

ML - Lecture 6.1 - Analysis and Evaluation of Classifier’s Performance

ML - Lecture 5 - Decision Tree

ML - Lecture 4.2 - Naive Bayes Classifier

ML - Lecture 4.1 - K-NN classifier

ML - Lecture 3.1 - Classification and Logistic Regression

ML - Lecture 3.2 - Overfitting and Regularization

ML - Lecture 2 - Gradient descent | Multiple features regression

Trees traversals | Binary Trees

Trees and implementation

Queue and circular queue

Cursor IMplementation | Stack

Linked list - Intro - add nodes

Algorithm Analysis 3 - Loops and Insertion sort

Algorithm Analysis 2 - Big-omega and Big-theta

Algorithm Analysis 1

25 - C programming - Pointers 2