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

H2o 3 ⭐ 6,618

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Orange3 ⭐ 4,469

🍊 📊 💡 Orange: Interactive data analysis

Flaml ⭐ 3,500

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Machine Learning With Python ⭐ 2,980

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Mljar Supervised ⭐ 2,867

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

Dtreeviz ⭐ 2,720

A python library for decision tree visualization and model interpretation.

Benchm Ml ⭐ 1,839

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Awesome Fraud Detection Papers ⭐ 1,364

A curated list of data mining papers about fraud detection.

Ai_all_resources ⭐ 647

A curated list of Best Artificial Intelligence Resources

Chefboost ⭐ 428

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

User Machine Learning Tutorial ⭐ 386

useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html

Miceforest ⭐ 265

Multiple Imputation with LightGBM in Python

The Python Workshop ⭐ 245

A New, Interactive Approach to Learning Python

Machine_learning_algorithms_from_scratch ⭐ 164

This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.

The Data Science Workshop ⭐ 156

A New, Interactive Approach to Learning Data Science

Youtube Like Predictor ⭐ 126

YouTube Like Count Predictions using Machine Learning

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

Betaml.jl ⭐ 83

Beta Machine Learning Toolkit

25daysinmachinelearning ⭐ 48

I will update this repository to learn Machine learning with python with statistics content and materials

Aiml Projects ⭐ 44

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

Random Forest Mc ⭐ 38

Random Forest with Dynamic Tree Selection Monte Carlo Based (RF-TSMC).

Machinelearningseries ⭐ 28

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

Machinelearning_breastcancer_python ⭐ 26

Machine Learning Applications using Sklearn, matplotlib, pandas, and seaborn

Accelerated Oblique Random Survival Forests

Forecast Of Time Series With Stock Data ⭐ 16

Comparative Analysis of Techniques for Forecasting Time Series in Financial Markets

Cic Ids 2018 ⭐ 16

CSE-CIC-IDS-2018 analyze with Random Forest

Predicting Baseball Statistics ⭐ 14

Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn

Implementation Of Ml Algos In Python ⭐ 13

Implementing various machine learning algorithm from scratch

Code and manual of the endoR R-package (Ruaud et al, in preparation).

Phishytics Machine Learning For Phishing ⭐ 12

Machine Learning for Phishing Website Detection

Artificial_curiosity ⭐ 12

Adaptive Reinforcement Learning of curious AI basketball agents

Machine Learning From Scratch ⭐ 12

🤖 Python implementations of some of the fundamental Machine Learning models and algorithms from scratch with interactive Jupyter demos and math being explained.

Machine Learning algorithms coded from scratch

Machine Learning Based - Intrusion Detection System

Oil_price ⭐ 11

Machine Learning to predict share prices in the Oil & Gas Industry

Tree.interpreter ⭐ 10

Decision tree interpreter for randomForest/ranger as described in

Mobile Price Prediction Classification Analysis ⭐ 10

Supervised Machine Learning Analysis Using Classification Models

Instagram Insights ⭐ 8

A jupyter notebook for extracting meaningful informations about your Instagram profile, like the best time to post and the hashtags that are generating more interactions

Randomforests ⭐ 8

Random Forest Library In Python Compatible with Scikit-Learn

Housing Rent Prediction ⭐ 6

End to End Machine Learning Project along with deployment.

Speakerclassifier ⭐ 6

A random forest classifier to predict the age-group and gender of a speaker from voice measurements.

Eco Fertilization ⭐ 6

Final year project based on Machine Learning

Porto Seguro Safe Driver Prediction ⭐ 6

Predict if a driver will file an insurance claim next year. (Kaggle Competition)

Hybrid Recommender System ⭐ 6

A repository for a machine learning project about creating a hybrid movie recommender system.

Risk_calculation_using_backward_elimination_algorithm_in_life_insurance ⭐ 6

Implementation of backward elimination algorithm used for dimensionality reduction for improving the performance of risk calculation in life insurance industry.

Cancer Detection ⭐ 5

Team Capybara final project "Histopathologic Cancer Detection" for the Statistical Machine Learning course @ University of Trieste

This Data Science-like project is aimed on analyzing a bunch of techniques for False Negatives (Frauds classified as Non-Frauds) in a extreme imbalanced dataset - Financial Fraud and improving the predictors performance.

Dimension Reduction Forests

Predict Which Customers A Call Center Should Contact ⭐ 5

Predict which customers should a call-center call for greater assertiveness in a sale

Recommended Bets By Email Mlb ⭐ 5

An advanced machine learning model utilizes a Random Forest Regressor to generate betting recommendations for Major League Baseball (MLB) games.

Pylearning ⭐ 5

Simple high-level machine-learning library in Python

Bank Marketing ⭐ 5

A Data-Driven Approach to Predict the Success of Bank Telemarketing

Nested Bigrams ⭐ 5

A repository containing the source code, datasets, and ranked features for the Nested Bigrams method proposed in a paper published in ICDMW. This method is designed for authorship attribution in source code to address cybersecurity issues.

Predictive Modeling In R ⭐ 5

Workshop (2-6 hours): cleaning, missing value imputation, EDA, ensemble learning, calibration, variable importance ranking, accumulated local effect plots. WIP.

Human Activity Recognition Smartphone Sensors ⭐ 5

Mini-project based on activity detection dataset at UCIML. Checkout branches for latest push.

Data Science Portfolio ⭐ 5

Portfolio of data science projects completed by me for self learning.Looking for job opportunity.

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