Name: Mehul Bhargava
Type: User
Company: Ministry of Education and Child Care, BC Public Services, Canada
Bio: | Data Science | Machine Learning | Software Development | Data Analysis |
Location: British Columbia, Canada
Mehul Bhargava's Projects
The aim of the whole project was to detect anomalies in the supercomputer logs based on certain events and messages, extracting critical features using feature engineering and running Random Forest Machine Learning model to evaluate the performance. It turned out to be a 99% accurate on test set using all the classification criteria - confusion matrix, precision, recall etc
The project aims to explore optimal machine learning models for predicting crop yield based on growing patterns at the township level using the Python programming language with its various libraries and packages for applying Deep Learning methods and algorithms
The Repository for the team DATA-INSIGHTERS participated in the BIRS-CIH-Hackathon.
OCP Training Workshop Material and Labs
🔥 A Complete List of GitHub Profile Badges and Achievements 🔥
A project based on Github API R wrapper package including functions for fetching the statistics of contributors/user of various repositories and also plotting the visualizations and time series plots.
A repository to keep my notes for Linux commands. Go through the commands and try them in your Linux terminal for better understanding and to take a look at the outputs for each of the commands.
Sample code to learn basics of Numpy and get familiar with it.
Python modules and packages to find appropriate property using different attributes and the related features using the concepts of object oriented programming
An app (dashboard) that enables the target audience to explore different sales metrics for each state to better understand what factors contribute to higher profit. This tool will help the marketing team target which category of products they should focus their efforts on.
This mini project focuses on the population count of several countries of the world. It gives users a GUI of the world map, representing countries with three different colours red, yellow and green based on their population count either overpopulated or moderate population or normal population.