m-clark

m-clark's Stars

• rasbt/LLMs-from-scratch

  Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

  Language:Jupyter Notebook36.1k3851084.5k

• sepandhaghighi/pycm

  Multi-class confusion matrix library in Python

  Language:Python1.5k36206126

• automl/TabPFN

  Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.

  Language:Python1.3k1683113

• slowkow/ggrepel

  :round_pushpin: Repel overlapping text labels away from each other in your ggplot2 figures.

  Language:R1.2k2521396

• JeffSackmann/tennis_atp

  ATP Tennis Rankings, Results, and Stats

  1k100217613

• grf-labs/grf

  Generalized Random Forests

  Language:C++98348508251

• mlr-org/mlr3

  mlr3: Machine Learning in R - next generation

  Language:R9532864186

• easystats/see

  :art: Visualisation toolbox for beautiful and publication-ready figures

  Language:R8932318045

• DavisVaughan/furrr

  Apply Mapping Functions in Parallel using Futures

  Language:R7022322240

• SebKrantz/collapse

  Advanced and Fast Data Transformation in R

  Language:C666923835

• strengejacke/ggeffects

  Estimated Marginal Means and Marginal Effects from Regression Models for ggplot2

  Language:R5721038036

• tidyverts/tsibble

  Tidy Temporal Data Frames and Tools

  Language:R5322626448

• vincentarelbundock/marginaleffects

  R package to compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and ML models. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference

  Language:R478121k48

• eliocamp/ggnewscale

  Multiple Fill, Color and Other Scales in `ggplot2`

  Language:TeX407116718

• rvlenth/emmeans

  Estimated marginal means

  Language:R3651248632

• vincentarelbundock/countrycode

  R package: Convert country names and country codes. Assigns region descriptors.

  Language:R3491225285

• markriedl/transformer-walkthrough

  A walkthrough of transformer architecture code

  Language:Jupyter Notebook3198439

• mlr-org/mlr3book

  Online version of Bischl, B., Sonabend, R., Kotthoff, L., & Lang, M. (Eds.). (2024). "Applied Machine Learning Using mlr3 in R". CRC Press.

  Language:TeX2571625959

• r-causal/causal-inference-in-R

  Causal Inference in R: A book!

  Language:TeX2021418654

• tunguz/TabularBenchmarks

  Language:Jupyter Notebook1968122

• etiennebacher/tidypolars

  Get the power of polars with the syntax of the tidyverse

  Language:R1854844

• mlr-org/mlr3extralearners

  Extra learners for use in mlr3.

  Language:R93518551

• facebookresearch/nbm-spam

  Training and evaluating NBM and SPAM for interpretable machine learning.

  Language:Python767714

• m-clark/models-by-example

  By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

  Language:R673017

• m-clark/book-of-models

  Spells for everyday living. (also a book coming out in 2025)

  Language:Jupyter Notebook5642013

• m-clark/polars-talk-2024

  Notebook for a talk introducing polars

  Language:Jupyter Notebook6201

• m-clark/distill-workshop

  This will introduce R users to the Distill format for R Markdown, for scientific communication and building websites.

  Language:R3301

• Michiana-R-Users-Group/MRUG_Projects

  A collection of topics and code from our MRUG meetings.

  Language:HTML330

• strongio/foundry

  Language:Python312130

• strongio/rust-ml-lab

  Intro to Rust for ML

  Language:Rust2400