Open source platform for the machine learning lifecycle

Natural Language Processing Best Practices & Examples

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

Koalas: pandas API on Apache Spark

股票AI操盘手：从学习、模拟到实盘，一站式平台。包含股票知识、策略实例、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易

This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more

DoEKS is a tool to build, deploy and scale Data & ML Platforms on Amazon EKS

Kickstart your MLOps initiative with a flexible, robust, and productive Python package.

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Crane is a easy-to-use and beautiful desktop application helps you build manage your container images.

Framework to bring LLM applications to production

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

All the available resources to master MLOPS from scratch

Ready to run docker-compose configuration for ML Flow with Mysql and Minio S3

Flexible and scalable template based on PyTorch Lightning + Hydra. Efficient workflow and reproducibility for rapid ML experiments.

A kedro-plugin for integration of mlflow capabilities inside kedro projects (especially machine learning model versioning and packaging)

[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.