mjimcua's Stars
shap/shap
A game theoretic approach to explain the output of any machine learning model.
cookiecutter/cookiecutter
A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.
dennybritz/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
fchollet/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
microsoft/nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Yorko/mlcourse.ai
Open Machine Learning Course
EpistasisLab/tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
aikorea/awesome-rl
Reinforcement learning resources curated
automl/auto-sklearn
Automated Machine Learning with scikit-learn
facebookresearch/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.
cs230-stanford/cs230-code-examples
Code examples in pyTorch and Tensorflow for CS230
mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
shankarpandala/lazypredict
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
scikit-learn-contrib/hdbscan
A high performance implementation of HDBSCAN clustering.
afshinea/stanford-cs-221-artificial-intelligence
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
shervinea/mit-15-003-data-science-tools
Study guides for MIT's 15.003 Data Science Tools
abhishekkrthakur/autoxgb
XGBoost + Optuna
shervinea/stanford-cme-106-probability-and-statistics
VIP cheatsheets for Stanford's CME 106 Probability and Statistics for Engineers
EpistasisLab/scikit-rebate
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
carl24k/fight-churn
Code from the book Fighting Churn With Data
scikit-learn-contrib/scikit-learn-extra
scikit-learn contrib estimators
EpistasisLab/scikit-mdr
A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
taknev83/pywedge
Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking
scpd-proed/General_Handouts
rsolanodev/holidays-es
A small Python package to obtain the public holidays in Spain from 2006 to the current year.
jmolina010/clasificador-de-datos-de-cancer-de-mama
kristiyanto/fintech-user-engagement
Defining, predicting, and preventing dropout users in fintech setting
jmolina010/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
jmolina010/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
jmolina010/voicebot-sencillo-en-Python
Es un notebook que implementa voice bot sencillo desarrollado íntegramente en Python