Multivariate stock price forecasting

Feature engineering package with sklearn like functionality

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

This Repository contains material to learn about machine learning algorithms concepts along with implementation. This also provides you the material to prepare yourself for interviews.

This project focuses on a comprehensive analysis of Netflix's stock market performance utilizing R programming. It involves data extraction, cleaning, and visualization to identify key trends and patterns. The objective is to provide actionable insights into Netflix's stock behaviour.

IbisML is a library for building scalable ML pipelines using Ibis.

OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

CANtropy: Time Series Feature Extraction-Based Intrusion Detection Systems for Controller Area Networks

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

Docs for Chalk AI

Python framework for interpretable protein prediction

Low code machine learning library, specified for insurance tasks: prepare data, build model, implement into production.

This repository contains code for predicting house sales prices using machine learning models. It includes data preprocessing, model training, evaluation, and prediction on test data.

Feature Engine for real-time AI/ML

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.

EvalML is an AutoML library written in python.

This is a collection of all the machine learning techniques required in any machine learning project. It contains detailed descriptions, videos, book recommendations, and additional material to properly grasp all the concepts.