scikit-learn

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

Fast and Accurate ML in 3 Lines of Code

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

A end-to-end MLOps pipeline for predicting telecom customer churn, featuring automated data preprocessing, ML model training, experiment tracking with MLflow, distributed training using PySpark, real-time inference via Kafka streaming, Airflow DAG orchestration, and Dockerized REST API deployment.

A curated list of project tutorials for project-based learning.

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

Symbolic Learning in Python and Julia