Name: Parmod Kumar, Ph.D.
Type: User
Company: Jiangxi University of Engineering
Bio: I am a qualified Engineer offering 16 years of cross-functional experience. Contact: [email protected], [email protected] and +91-7838779082.
Twitter: ParmodKumar
Location: Jiangxi, China
Blog: https://sites.google.com/site/parmodkumarphd2011/
Parmod Kumar, Ph.D.'s Projects
Notebooks for "Python for Signal Processing" book
python image processing program
Python Data Science Handbook: full text in Jupyter Notebooks
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A package of documentation and software supporting MATLAB/Simulink based dynamic modeling and simulation of quadcopter vehicles for control system design
Spatial data in R: using R as a GIS
R for data science
Toolkit for building predictive workflows on the top of pandas and scikit-learn.
RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.
Homepage for the Robert Bosch Centre for Data Sciences & Artificial Intelligence at IIT Madras
Peer Assessment 1 for Reproducible Research
Statistical Rethinking course and book package
Robot Control using PID Controller and Kalman Filter
scikit-learn: machine learning in Python
Scripts for different meetups of ML-India (ml-india.org) | Gurgaon Chapter.
Udacity Self-Driving Car Engineer Nanodegree projects.
Shoe polishing project at Innopolis University, Double summer school on Robotics and SE 2018
SigViewer is a viewing application for biosignals.
Data sets for machine learning in Python
Scikit-Learn Tutorial for PyData Seattle 2015
Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.
Official repository for Spyder - The Scientific Python Development Environment
VIP cheatsheets for Stanford's CS 229 Machine Learning
machine learning course programming exercise
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial
Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison
Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"
Sequential Decision Problem Modeling Library @ Castle Lab, Princeton Univ.
This repo has all the related materials to meetups