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advanced-forecasting-python

Source Code for 'Advanced Forecasting with Python' by Joos Korstanje

advertisement-performance-prediction

aiml-projects

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

amazing-feature-engineering

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

anomaly-detection-using-k-means-clustering

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

bookrepo

business-machine-learning

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)

campaign-modeling

computervision

contract_extraction_gpt

coursera-r-programming

Notes from the R programming Coursera course

dominance-analysis

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

dsprojects

eda

Project - MovieLens Data Analysis - EDA

ensemble-methods

exploratory_data_analysis

This is a repository for any and all code written for the Exploratory Data Analysis Coursera course through Johns Hopkins University.

getting_and_cleaning_data

This is a repository for any and all code written for the Getting and Cleaning Data Coursera course through Johns Hopkins University.

hackerrank-data-science

Data Science/Machine Learning Solutions in Python3

hackerrank-data-scientist-hiring-test

Predict life expectancy of a country or a geographical area based on socioeconomic factors.

hands-on-exploratory-data-analysis-with-python

Hands-on Exploratory Data Analysis with Python, published by Packt

hommmer

A simple Marketing Mix Modeling library for Python

lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

lightweightmmm

Create an MMM for your company using Google's Lightweight MMM

ml-webinar

Machine Learning with sklearn tutorials (for Pearson)

mmm_stan

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

natural-language-processing-recipes

Source Code for 'Natural Language Processing Recipes' by Akshay Kulkarni and Adarsha Shivananda

neuralnetwork

nlp

numpy_python