mjimcua

autoxgb

XGBoost + Optuna

shap

A game theoretic approach to explain the output of any machine learning model.

stanford-cs-221-artificial-intelligence

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

pywedge

Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking

holidays-es

A small Python package to obtain the public holidays in Spain from 2006 to the current year.

mljar-supervised

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

fintech-user-engagement

Defining, predicting, and preventing dropout users in fintech setting

tpot

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

scikit-rebate

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

scikit-mdr

A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.

fight-churn

Code from the book Fighting Churn With Data

auto-sklearn

Automated Machine Learning with scikit-learn

awesome-rl

Reinforcement learning resources curated

mlcourse.ai

Open Machine Learning Course

Kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

cookiecutter

A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.

cs230-code-examples

Code examples in pyTorch and Tensorflow for CS230

mit-15-003-data-science-tools

Study guides for MIT's 15.003 Data Science Tools

General_Handouts

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

lazypredict

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

stanford-cme-106-probability-and-statistics

VIP cheatsheets for Stanford's CME 106 Probability and Statistics for Engineers

scikit-learn-extra

scikit-learn contrib estimators

hdbscan

A high performance implementation of HDBSCAN clustering.

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

clasificador-de-datos-de-cancer-de-mama

GAN_fashion_mnist_explained

Este notebook trata de explicar la filosofía y objetivo de las redes GAN -Generative Adversarial Networks- a partir de un ejemplo básico que genera imágenes de prendas de vestir y complementos basadas en el conjunto Fashion MNIST

voicebot-sencillo-en-Python

Es un notebook que implementa voice bot sencillo desarrollado íntegramente en Python

analisis-de-textos-con-Python

Ejemplo de cómo pueden analizarse textos mediante Python con NLTK y Spacy para valorar el tipo de contenido predominante en los mismos