📊 R Programming Fundamentals: An In-Depth Guide with Comments
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Updated
Jun 11, 2024 - R
📊 R Programming Fundamentals: An In-Depth Guide with Comments
Efficient Variable Selection for GLMs in R
Regression Models for Epidemiology
A statistics package with a variety of bootstrap and other resampling tools
Statistical Machine Intelligence & Learning Engine
[ICLR 2024] SemiReward: A General Reward Model for Semi-supervised Learning
The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.
Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.
Rust library for quantitative finance.
Some of the topics, algorithms and projects in Machine Learning & Deep Learning that I have worked on and become familiar with.
Benchmark a given function for variable input sizes and find out its time complexity
The PROCESS module
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
Data Science, ML & DL Notebooks
My Jupyter notebooks in which I practice data science.
Regression model building and forecasting in R
Machine learning and data analysis package implemented in JavaScript and its online demo.
Network Performance Framework: easy-to-use experiment manager with automated testing, result collection, and graphing
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