Discover how to turn and infer correlation between variables into causation.

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

Forecasting daily sales unit for slow selling SKUs using techniques such as Croston, LGBM, XGB, ARIMA, Moving Average etc.

Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity

Machine Learning for Imbalanced Data, published by Packt

Causal Inference and Discovery in Python by Packt Publishing

Build an scikit-learn model to predict churn using customer telco data.

CPSC 330: Applied Machine Learning

Salary Prediction Web App With Streamlit

Schedule a Python script with GitHub Actions

Different tutorials how to deploy Machine Learning models

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

During our extending spring break, I decided to start getting hands on training with Machine Learning in Tensorflow. I will cover what I have learned Machine Learning with Tensorflow course taughtr…

Jupyter notebooks for the Natural Language Processing with Transformers book

An object oriented approach to develop ETL pipelines, train machine learning/deep learning models and easy inference along with API endpoints implemented using pyramid web framework with Swagger UI…

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…

My main Machine Learning class

Data Science: Principles and Practice, 2020-21

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

Practice your pandas skills!

Source code of the Apache Airflow Tutorial for Beginners on YouTube Channel Coder2j (https://www.youtube.com/c/coder2j)

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

DataCamp course excercises

Learn ML engineering for free in 4 months! Register here 👇🏼