bhaskar-jr Goto Github PK

10-weeks

10-weeks of technology exploration

100-days-of-ml-code

100 Days of ML Coding

120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

2015lab3

2015lab4

Lab for Linear and Logistic Regression, SciKit Learn

2015lab7

Decison Trees, Random Forrests, Ensemble Methods

2020_notes

A collection of notes regarding various topics. (Bash, PyTorch, Spark, etc.)

3d-iris-plot

a_b_testing

A/B test to determine the better marketing Campaign

anatomyofmatplotlib

Anatomy of Matplotlib -- tutorial developed for the SciPy conference

approaching-any-machine-learning-problems

Contains the note for the Approaching(Almost) any Machine Learning Problem by Abhishek Thakur.

arauto

An open-source tool for quick Time Series Analysis and Forecasting

ariawase

Ariawase is free library for VBA cowboys.

automaticreportingblog

Project for my "Using R for Immediate Reporting in Evaluation" blog post

automobile-dataset-analysis

This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price

awesome-dash

A curated list of awesome Dash (plotly) resources

awesome-swift

A collaborative list of awesome Swift libraries and resources. Feel free to contribute!

awesome_time_series_in_python

This curated list contains python packages for time series analysis

best-data-science-resources

This repository contains the best Data Science free hand-picked resources to equip you with all the industry-driven skills and interview preparation kit.

bhaskar-jr.github.io

categorical-data

Data sets for "An Introduction to Categorical Data Analysis" and "Categorical Data Analysis", 3rd editions

changhsinlee.github.io

Build a Jekyll blog in minutes, without touching the command line.

cheatsheets

RStudio Cheat Sheets

cluster_for_pubg

Analysis the behaviour of players in PUBG solo top100 by kmeans cluster algorithm.

clustering-by-silhouette

Optimize clustering labels using Silhouette Score.

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

coms4995-s20

COMS W4995 Applied Machine Learning - Spring 20

concrete-compressive-strength-prediction

Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the appropriate concrete for bridges, houses construction.

congress

Public domain data collectors for the work of Congress, including legislation, amendments, and votes.

content

Official content for Harvard CS109