Notebooks - A starter kit for Jupyter notebooks and machine learning. Companion docker images consist of all combinations of python versions, machine learning frameworks (Keras, PyTorch and Tensorflow) and CPU/CUDA versions.

Introduction | Weaviate documentation

About weaviate

Collaborative Machine Learning development | MLReef

A centralized platform to host run and track your machine learning work using built in pipelines containerized community scripts and fully versioned experiment tracking

Vector Database for Similarity Search | Pinecone

Search through billions of items for similar matches to any object in milliseconds it s the next generation of search an api call away

AI/ML Papers with Code Everywhere - CatalyzeX

Get implementation code for machine learning research papers with code directly on google ar xiv scholar twitter github etc

ML Workspace - All-in-one web-based IDE for machine learning and data science. The workspace is deployed as a docker container and is preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch) and dev tools (e.g., Jupyter, VS Code).

DVC - Data Science Version Control is an open-source version control system for machine learning projects with pipelines support. It makes ML projects reproducible and shareable.

DVClive - Python library for experiment metrics logging into simply formatted local files.

Kedro - Kedro is a data and development workflow framework that implements best practices for data pipelines with an eye towards productionizing machine learning models.

Guild AI - Better models by measuring

Guild ai is an open source experiment tracking toolkit use it to build better machine learning models faster

Sacred - Python tool to help you configure, organize, log and reproduce experiments. Like a notebook lab in the context of Chemistry/Biology. The community has built multiple add-ons leveraging the proposed standard.

MLflow - A platform for the machine learning lifecycle

An open source platform for the end to end machine learning lifecycle

Weights & Biases – Developer tools for ML

Wand b is a central dashboard to keep track of your hyperparameters system metrics and predictions so you can compare models live and share your findings

Machine Learning with TensorFlow, Second Edition

Updated with new code new projects and new chapters machine learning with tensor flow second edition i gives readers a solid foundation in machine learning concepts and the tensor flow library written by nasa jpl deputy cto and principal data scientist chris mattmann all examples are accompani

m2cgen - A tool that allows the conversion of ML models into native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart) with zero dependencies.

CML - A library for doing continuous integration with ML projects. Use GitHub Actions & GitLab CI to train and evaluate models in production like environments and automatically generate visual reports with metrics and graphs in pull/merge requests. Framework & language agnostic.

Pythonizr - Machine Learning Development Tool!

Pythonizr generates clean customizable machine learning python code with just what you need to start quickly

Flyte

Flyte enables production grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production