Pinned Repositories
competitive-data-science
Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course
COVID-Medium-article
CV-portfolio
I got an equal mix of exposure to Industry and Academics in my working life. I am passionate about developments in the field of Data Science and believes that responsible applications will help solve a number of problems the society faces now. I enjoy teaching and training. Currently I focus a lot these activities and continue to receive excellent feedbacks.
deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
GWU_data_mining
Materials for GWU DNSC 6279 and DNSC 6290.
ML-and-Statistics-Notebooks
Understanding-ROC
Codes used for simulation mentioned in the article
regivm's Repositories
regivm/GWU_data_mining
Materials for GWU DNSC 6279 and DNSC 6290.
regivm/ML-and-Statistics-Notebooks
regivm/Understanding-ROC
Codes used for simulation mentioned in the article
regivm/competitive-data-science
Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course
regivm/COVID-Medium-article
regivm/CV-portfolio
I got an equal mix of exposure to Industry and Academics in my working life. I am passionate about developments in the field of Data Science and believes that responsible applications will help solve a number of problems the society faces now. I enjoy teaching and training. Currently I focus a lot these activities and continue to receive excellent feedbacks.
regivm/deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
regivm/Electric_Vehicle
Comparison between EV and Fuel Vehicles
regivm/featexp
Feature exploration for supervised learning
regivm/free-programming-books
:books: Freely available programming books
regivm/Hands-On-Natural-Language-Processing-with-Python
This repository is for my students of Udemy. You can find all lecture codes along with mentioned files for reading in here. So, feel free to clone it and if you have any problem just raise a question.
regivm/machine-learning-project-walkthrough
An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!
regivm/Machine-Learning-with-Python
Python codes for common Machine Learning Algorithms
regivm/Marketing-Research-Notebooks
regivm/ML-Experiments
Notebooks covering a number of Machine Learning algorithms.
regivm/ML_Datasets
regivm/ModSimPy
Text and supporting code for Modeling and Simulation in Python
regivm/NLP
Natural Language Processing
regivm/regivm.github.io
pages
regivm/seaborn-data
Data repository for seaborn examples
regivm/SmartScience
regivm/stat479-machine-learning-fs19
Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison
regivm/udemy-feml-challenge