#typescript #data_visualization #database #database_schema #documentation #documentation_tool #entity_relationship_diagram #er_diagram #erd #nodejs #orm #postgresql #prisma #react_flow #reactjs #ruby_on_rails #sql #tbls #typescript #visualization #webassembly

Liam ERD is a tool that helps you create easy-to-understand diagrams of your database. It makes interactive diagrams that you can zoom in and out of, filter, and explore easily. This tool is useful for both small and large projects, handling over 100 tables with ease. It's simple to set up and is open-source, meaning you can contribute to it. Using Liam ERD helps you visualize complex database structures quickly, making it easier to understand and work with your data. This saves time and reduces errors compared to drawing diagrams manually.

https://github.com/liam-hq/liam

#other #automl #chatgpt #data_analysis #data_science #data_visualization #data_visualizations #deep_learning #gpt #gpt_3 #jax #keras #machine_learning #ml #nlp #python #pytorch #scikit_learn #tensorflow #transformer

This is a comprehensive, regularly updated list of 920 top open-source Python machine learning libraries, organized into 34 categories like frameworks, data visualization, NLP, image processing, and more. Each project is ranked by quality using GitHub and package manager metrics, helping you find the best tools for your needs. Popular libraries like TensorFlow, PyTorch, scikit-learn, and Hugging Face transformers are included, along with specialized ones for time series, reinforcement learning, and model interpretability. This resource saves you time by guiding you to high-quality, actively maintained libraries for building, optimizing, and deploying machine learning models efficiently.

https://github.com/ml-tooling/best-of-ml-python

#typescript #data_visualization #geospatial_analysis #javascript #maps #python #visualization #webgl

deck.gl is a powerful tool that helps you create fast, interactive, and visually impressive maps and data visualizations using WebGL technology. It lets you turn large sets of data into layers like icons, polygons, and text, which you can view in different ways such as maps or 3D scenes. It works well with popular map providers like Google Maps and Mapbox, and supports easy interaction like clicking and filtering. You can use it simply by adding a script or installing it via npm or Python. This makes it easier for you to build custom, high-performance visualizations quickly and with less coding effort.

https://github.com/visgl/deck.gl