JSchoeck's Stars
pycaret/pycaret
An open-source, low-code machine learning library in Python
datamllab/tods
TODS: An Automated Time-series Outlier Detection System
drivendataorg/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
elena-sharova/IsolationForest
testing scikit-learn Isolation Forest
yzhao062/anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
yzhao062/SUOD
(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)
yzhao062/MetaOD
Automating Outlier Detection via Meta-Learning (Code, API, and Contribution Instructions)
8080labs/ppscore
Predictive Power Score (PPS) in Python
Azure/AI-PredictiveMaintenance
ajayarunachalam/msda
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
AileenNielsen/TimeSeriesAnalysisWithPython
weibullguy/python-lint-plus
GitHub Action to QA Your Python Code
konstruktoid/action-pylint
A GitHub action that checks Python code using black and ruff
akridge/Valheim-Free-Game-Server-Setup-Using-Oracle-Cloud
Valheim Oracle Cloud Server Setup
khuyentran1401/awesome-Python-data-science-books
Probably the best curated list of data science books in Python
ericagol/TRAPPIST1_Spitzer
TRAPPIST-1 TTVs and Spitzer photodynamics
Yimeng-Zhang/feature-engineering-and-feature-selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
chiphuyen/just-pandas-things
An ongoing list of pandas quirks
alfranz/frnz-sample
A sample package structure for the personal Data Science toolkit 🧰🛠💥
dbader/readme-template
README.md template for your open-source project
eugeneyan/ml-surveys
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
frenck/awesome-home-assistant
A curated list of amazingly awesome Home Assistant resources.
eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
alexeygrigorev/data-science-interviews
Data science interview questions and answers
khuyentran1401/Data-science
Collection of useful data science topics along with articles, videos, and code
mml-book/mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
Building-ML-Pipelines/building-machine-learning-pipelines
Code repository for the O'Reilly publication "Building Machine Learning Pipelines" by Hannes Hapke & Catherine Nelson
aric-hamburg/brown-bag-sessions
Remote Brown Bag Sessions des ARIC