Improve Project Catalyst with insights gained through data collection and analysis, machine learning and AI.
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Updated
May 19, 2024 - Python
Improve Project Catalyst with insights gained through data collection and analysis, machine learning and AI.
History of BuyVM/BuyShared/Frantech stock data scraped from buyvmstock.com & buyvm.hasstock.net
This is a repository to extract different metrics from the OpenManage Enterprise service running in a Dell cluster
The Open Source Time-Series Data Historian
Zerda AI framework | Cross-platform | Modular | Wide GPU support
A unified framework for machine learning with time series
Chrome Extension, download photos, videos from Instagram post, tv, reels, stories
A rules induction system for data mining and exploratory data analysis
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
A toolkit for machine learning from time series
This data analysis notebook demonstrates lossless, lossy visualizations techinques and classification methods. We demonstrate analysis of scientific data on hot-swappable datasets.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
sciBASIC# is a kind of dialect language which is derive from the native VB.NET language, and written for the data scientist.
C# KQL query engine with flexible I/O layers and visualization
Topic Modelling for Humans
AI Enhanced DataHive embarks on a mission to become a centralized hub for data of various kinds, offering templates for collectors to aggregate data centrally for further processing in other applications. This initiative arises from the repeated cycles of developing crawlers, extractors, and collectors across numerous projects.
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
Astrostatistics and Machine Learning class for the MSc degree in Astrophysics at the University of Milan-Bicocca (Italy)
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