#typescript#embedding#visualization
Embedding Atlas is a powerful tool that helps you easily visualize and explore large sets of data points called embeddings. It automatically groups and labels data, shows dense areas and outliers clearly, and lets you search for similar items in real time. It works fast even with millions of points using modern web technology and can be used in Python, Jupyter notebooks, or web apps. This means you can better understand complex data, find patterns, and make decisions faster without complicated setup or slow performance. It’s open source and privacy-friendly since your data stays on your device.
https://github.com/apple/embedding-atlas
http://www.csestack.org/python-libraries-for-data-science/
As per the DIKW Pyramid Model, #Data_Science job revolves around finding the information, knowledge from Raw Data. And it can be bundled into the stack of 4 entities:
source of #data
manage and store data
analyze the data
display analyzed output (#visualization, statistics)
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
#Scikit_learn is an open source Python library that implements a range of #machine_learning , preprocessing, cross-#validation and #visualization algorithms using a unified interface...