sciBASIC# is a kind of dialect language which is derive from the native VB.NET language, and written for the data scientist.
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Updated
Jun 11, 2024 - Visual Basic .NET
sciBASIC# is a kind of dialect language which is derive from the native VB.NET language, and written for the data scientist.
Chrome Extension, download photos, videos from Instagram post, tv, reels, stories
This is a repository to extract different metrics from the OpenManage Enterprise service running in a Dell cluster
History of BuyVM/BuyShared/Frantech stock data scraped from buyvmstock.com & buyvm.hasstock.net
A unified framework for machine learning with time series
Univariate Time-Series Anomaly Detection algorithms from TSB-UAD
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.
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python
Singer tap for ClinicalTrials.gov study records data.
A toolkit for machine learning from time series
A Deep Learning Python Toolkit for Healthcare Applications.
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.
This is a repository that I have created to showcase skills and share projects in Business Analytics.
Anyone (including beginners) can use these resources to get started with accessing, cleaning, and analysing different kinds of data in Python. No installation required. No registration required.
📝 An awesome Data Science repository to learn and apply for real world problems. With repository stars⭐ and forks🍴
AIL framework - Analysis Information Leak framework
C# KQL query engine with flexible I/O layers and visualization
Simulations for the paper "Inter node Hellinger Distance based Decision Tree by Pritom Saha Akash, Md. Eusha Kadir, Amin Ahsan Ali, Mohammad Shoyaib"
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