Machine Learning (Python and R)

My Github repositories MachineLearning_Python and MachineLearning_R are collection of various machine learning algorithms implemented in both python and in R. The algorithms include:

Regression: Support Vector Regression, Decision Tree Regression, Linear Regression, Polynomial Regression, Neural Network Regression, and Random Forest Regression.

Classification: Logistic Regression, Support Vector Machines, Random Forest, Decision Trees, Naive Bayes, k Nearest Neighbours, Neural Networks

Clustering: k-means clustering, Hierarchical clustering

Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

Dimensionality Reduction: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA)

Deep Learning (PyTorch, TensorFlow and Keras)

This GitHub repository includes the codes of several deep learning architectures such as MLP, RNN, LSTM, CNN implemented using different frameworks such as pyTorch, Tensorflow and Keras for both CPU and GPU.​ The codes of aforementioned deep learning architectures are also implemented from scratch without any frameworks and is available.

Progressive Learning, Universal Classifier

A brief description of the various research works during my PhD including progressive learning technique for multi-class, multi-label and label-independent classifier along with their related publications and links to source code are provided under PhD Research section of the website