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ab_test_guide_in_python

bishalneogi

Config files for my GitHub profile.

blp-demand-estimation

Python code for BLP (Berry, Levinsohn and Pakes) method of structural demand estimation using the random-coefficients logit model. Code for estimation of demand and supply-side moment jointly is also provided.

car-price-prediction-linear-regression

Machine learning model with linear regression for car price prediction

dailyknowledge

This repository contains the files and resources from my Daily Knowledge hunt

data-analysis-with-r

Using gglot2, tidyr, dplyr, ggmap, choroplethr, shiny, logistic regression, clustering models and more

data-science-series

For all those who're struggling to find a good hands-on resource (with case studies) to master their Data Science skills, Here's all what you need!

decision-tree-splits-continuous-variables

A simple example to answer - how is a splitting point chosen for continuous variables in decision trees?

decision-trees

Decision Tree using Titanic dataset

dimension-reduction-techniques

Contains worked examples of Dimension reduction techniques to solve ML problems

dplyr-tutorial

Tutorials for the dplyr package in R

eda

All possible ways to simplify and accommodate data explorations

eda_and_beyond

Library of small tools for EDA and Modeling

edmdemandelast

Script to estimate demand elasticities via LA-AIDS model and generate standard errors via bootstrapping. Cite as Jason J. Holderieath. (2016). Demand Elasticity Estimation Using AIDS Model and Bootstrapped Standard Errors [Data set]. Zenodo. http://doi.org/10.5281/zenodo.192384

how-to-become-a-ds-in-30-days

How to become a data scientist in 30 days

isl_python

An Introduction to Statistical Learning with Applications in PYTHON

islr-answers

Solutions to exercises from Introduction to Statistical Learning (ISLR 7th Edition)

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

logistic_regression_rare_events

This repo is a short exercise comparing weighted MLE (using the sample weights option in sklearn) versus stratified random over sampling of the rare class.

market-mix-modelling

This repository contains the code and explanation for market mix modelling technique in economics

ml-forecast-features-eng

Machine Learning for Retail Sales Forecasting — Features Engineering

mlops_gokumohandas

Learn how to design, develop, deploy and iterate on production-grade ML applications.

mmm_stan

Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

new_product_reco

r-bootcamp

r4ds

R for data science: a book

recommender-tutorial

An introduction to recommendation systems in Python

statistical-data-analysis-using-r

Intro to Statistical Data Analysis using R

tars_mba

TARS based prediction for Next Basket