susenjitee,Susenjit Ghosh,github

amazing-feature-engineering

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

aue893_robust_predictive_control

This repository contains classwork and practice examples based on Model Predictive Control. Robust and Stochastic control methods applied to and studied for linear/non-linear plants.

bayesian-machine-learning

Notebooks related to Bayesian methods for machine learning

benchmark-mpc-problems

Open collection of model predictive control (MPC) benchmarking problems

databook_matlab

Matlab files with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz http://www.databookuw.com/

databook_python

IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz

ensemble-machine-learning

Code repository for Ensemble Machine Learning, published by Packt

ensemble-machine-learning-cookbook

Ensemble Machine Learning Cookbook, published by Packt

estimation-of-remaining-useful-life-using-cnn

Convolutional Neural Network based regression approach for estimating machinery's remaining useful life

falcopt

First-order Algorithm via Linearization of Constraints for OPTimization

feature-selection

It contains some of the novel feature selection algorithms I've developed

feature-selection-algorithm

Code for Feature Selection

feature-selection-for-machine-learning

Code Repository for the online course Feature Selection for Machine Learning

hilbert-huang-transform

A demo of using Hilbert-Huang Transform (HHT) for non-stationary and non-linear signal analysis.

hilbert-huang-transform-1

Implementation of Hilbert-Huang Transform software for matlab.

hyperparameter-optimization-of-machine-learning-algorithms

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

matlab-dmd

Dynamic Mode Decomposition (DMD)

onlineemd

MATLAB Implementation of Online Empirical Mode Decomposition

pydmd

Python Dynamic Mode Decomposition

pyemd

Python implementation of Empirical Mode Decompoisition (EMD) method

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

vehicle-dynamics-lateral

OpenVD: Vehicle Dynamics - Lateral

wrapper-feature-selection-toolbox

This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

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