Navdeep Gill

autoviz. Leland Wilkinson's engine for automatic visualizations of tabular datasets

openclaw. Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞

doomarena-lab. Lightweight lab to run grounded agent security/safety experiments with SHIM demos now and REAL adapters as they’re available.

KVSplit. Run larger LLMs with longer contexts on Apple Silicon by using differentiated precision for KV cache quantization. KVSplit enables 8-bit keys & 4-bit values, reducing memory by 59% with <1% quality loss. Includes benchmarking, visualization, and one-command setup. Optimized for M1/M2/M3 Macs with Metal support.

reticulate. R Interface to Python

AIR_AI_Engineering_Course. Repo for AI Republic's AI Engineering Course - Winter 2024

gai_risk_management. A place for ideas and drafts related to GAI risk management.

LLM-Evals-Catalogue. This repository stems from our paper, “Cataloguing LLM Evaluations”, and serves as a living, collaborative catalogue of LLM evaluation frameworks, benchmarks and papers.

h2o-wizardlm. Open-Source Implementation of WizardLM to turn documents into Q:A pairs for LLM fine-tuning

h2o-llmstudio. H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://docs.h2o.ai/h2o-llmstudio/

h2ogpt. Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/

Made-With-ML. Learn how to develop, deploy and iterate on production-grade ML applications.

solas-ai-disparity. A Python Library of Curated Disparity Testing Metrics for Use in Real-World Settings

TalkToModel. TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!

inFairness. PyTorch package to train and audit ML models for Individual Fairness

nitro. Create apps 10x quicker, without Javascript/HTML/CSS.

proxy-methodology. Stata

phd-thesis. My UC Berkeley Ph.D. dissertation (2015).

imodels. Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

samplemod. Python

wave-apps. Sample AI Apps built with H2O Wave.

aequitas. Bias Auditing & Fair ML Toolkit

rchitect. Interoperate R with Python

interpret-community. Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world datasets and workflows.

wave. Realtime Web Apps and Dashboards for Python and R

GWU_rml. Jupyter Notebook

Mojave-Dark-RStudio-Theme. A Total-IDE Dark RStudio Theme inspired by Apple's dark aestheticcc.

openbrowser. Let AI agents browse the web. An autonomous toolkit for browser-based AI agents.

dabl. Data Analysis Baseline Library

article-information-2019. Article for Special Edition of Information: Machine Learning with Python

ai-deadlines. :alarm_clock: AI conference deadline countdowns

course-nlp. A Code-First Introduction to NLP course

rscodeio. An RStudio theme inspired by Visual Studio Code.

DrWhy. DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.

automlbenchmark. OpenML AutoML Benchmarking Framework

responsible_xai. Guidelines for the responsible use of explainable AI and machine learning.

SDSS2019. Materials for SDSS 2019, Bellevue WA

awesome-interpretable-machine-learning. Python

interpret. Fit interpretable models. Explain blackbox machine learning.

gitignore. A collection of useful .gitignore templates

explain-ml-pricing. Towards Explainability of Machine Learning Models in Insurance Pricing

secure_ML_ideas. Practical ideas on securing machine learning models

h2oworld_sf_2019. Human-Centered ML Presentation for H2O World SF 2019.

awesome-machine-learning-on-source-code. Cool links & research papers related to Machine Learning applied to source code (MLonCode)

kaggle-cli. Official Kaggle CLI

tidypredict. Run predictions inside the database

plumber. Turn your R code into a web API.

nbdime. Tools for diffing and merging of Jupyter notebooks.

pygbm. Experimental Gradient Boosting Machines in Python with numba.

open-product-management. A curated list of product management advice for technical people.

facets. Visualizations for machine learning datasets

sparkxgb. R interface for XGBoost on Spark

bad-data-guide. An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.

spinningup. An educational resource to help anyone learn deep reinforcement learning.

xai_misconceptions. Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!

xgboost-predictor-java. Pure Java implementation of XGBoost predictor for online prediction tasks.

nbastatR. NBA Stats API Wrapper and more for R

ggrough. Convert ggplot2 chart to roughjs

happy-git-with-r. Using Git and GitHub with R, Rstudio, and R Markdown

the-r-in-spark. Mastering Apache Spark with R

sourcetools. Tools for reading, tokenizing, and parsing R code.

esquisse. RStudio add-in to make plots interactively with ggplot2

code. Rust

Getting-Started-in-R. An 8 page guide to starting with R - Tidyverse Edition

faker. A library for generating fake data such as names, addresses, and phone numbers.

what-they-forgot. "What They Forgot to Teach You About R" website / eBook

awesome-production-machine-learning. A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

jsm_2018_paper. Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539

pwc. This repository is no longer maintained.

og. Oglang - Language that compiles to Golang

data.table-tutorial-uros2018. R

ToolsOfTheTrade. Tools of The Trade, from Hacker News.

zermelo. A radix sorting library for Go (golang)

Metrics. An R package for common supervised machine learning metrics.

TensorFlow-Examples. TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

cheatsheets. Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.

datasharing. The Leek group guide to data sharing

100-Days-Of-ML-Code. 100 Days of ML Coding

dowhy. DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Deep-Learning-Roadmap. :satellite: Organized Resources for Deep Learning Researchers and Developers

RSQLite. R interface for SQLite

altair. Declarative visualization library for Python

gganimate. A Grammar of Animated Graphics

py_ml_utils. Some small utility modules to help with pandas, numpy and sklearn usage in other projects

jsReact. R package: Modelling in R. Interactivity in JS. Best of both worlds.

usethis. Set up commonly used 📦 components

iml. iml: interpretable machine learning R package

autokeras. AutoML library for deep learning

r-pkg-intro. How to create an R package

h2oclient-java. Java REST API client for the H2O machine learning platform

yellowbrick. Visual analysis and diagnostic tools to facilitate machine learning model selection.

awesome-serverless. :cloud: A curated list of awesome services, solutions and resources for serverless / nobackend applications.

tech-interview-handbook. Curated coding interview preparation materials for busy software engineers

tmux. tmux source code

awesome-Interpretable-ML. A curated list for interpretable machine learning

awesome-public-datasets. A topic-centric list of HQ open datasets.

NLP-progress. Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

awesome-machine-learning-interpretability. A curated list of awesome responsible machine learning resources.

aa. Cliff Click Language Hacking

bench. High Precision Timing of R Expressions

DALEX. moDel Agnostic Language for Exploration and eXplanation

autoxgboost. autoxgboost - Automatic tuning and fitting of xgboost

interpretable_machine_learning_with_python. Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

h2o4gpu. H2Oai GPU Edition

docker-replay. Generate docker commands to rerun existing containers

anchor. Code for "High-Precision Model-Agnostic Explanations" paper

shap. A game theoretic approach to explain the output of any machine learning model.

rstudio. RStudio is an integrated development environment (IDE) for R

Rperform. :bar_chart: R package for tracking performance metrics across git versions and branches.

prophet. Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

tensorflow. An Open Source Machine Learning Framework for Everyone

json. JSON for Modern C++

git-flight-rules. Flight rules for git

interpretable-ml-book. Book about interpretable machine learning

thrust. [ARCHIVED] The C++ parallel algorithms library. See https://github.com/NVIDIA/cccl

mli-resources. H2O.ai Machine Learning Interpretability Resources

GWU_data_mining. Materials for GWU DNSC 6279 and DNSC 6290.

h2o. For the "Practical Machine Learning with H2O" book, to be published by O'Reilly (ISBN, etc. coming soon)

keras3. R Interface to Keras

Distrace. Monitoring Tool for Distributed Java Applications

packagemetrics. A Package for Helping You Choose Which Package to Use

datatable. A Python package for manipulating 2-dimensional tabular data structures

deep-learning-book. Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

awesome-random-forest. Random Forest - a curated list of resources regarding random forest

rsparkling. RSparkling: Use H2O Sparkling Water from R (Spark + R + Machine Learning)

tpot. A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

sonnet. TensorFlow-based neural network library

StackNet. StackNet is a computational, scalable and analytical Meta modelling framework

Deep-Learning-Papers-Reading-Roadmap. Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

awesome-python. An opinionated list of Python frameworks, libraries, tools, and resources

sparklyr. R interface for Apache Spark

fst. Lightning Fast Serialization of Data Frames for R

python-education. Reading list for ramping up with professional Python

mlr. Machine Learning in R

optunity. optimization routines for hyperparameter tuning

h2o-hyperopt. Library for integrated use of H2O with Hyperopt

sparklingwater. Sparkling Water for R

wikitables. Import tables from any Wikipedia article as a dataset in Python

ranger. A Fast Implementation of Random Forests

xgboost. Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

d3-examples-creators-talk. links for the talk d3.oakland( "Examples & Creators")

h2o-tutorials. Tutorials and training material for the H2O Machine Learning Platform

unconf16. rOpenSci's San Francisco hackathon/unconf 2016

scikit-learn. scikit-learn: machine learning in Python

hts. Hierarchical and Grouped Time Series

anomalous. Anomalous time series package for R

anomalous-acm. Anomalous time series package for R (ACM)

forecast. Forecasting Functions for Time Series and Linear Models

awesome-R. A curated list of awesome R packages, frameworks and software.

awesome-machine-learning. A curated list of awesome Machine Learning frameworks, libraries and software.

vowpal_wabbit. Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

wesanderson. A Wes Anderson color palette for R

SuperLearner. Current version of the SuperLearner R package

caret. caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models

MLBase.jl. A set of functions to support the development of machine learning algorithms

Distributions.jl. A Julia package for probability distributions and associated functions.

rHealthDataGov. R interface to the HealthData.gov Data API

ReScience. The ReScience journal. Reproducible Science is Good. Replicated Science is better.

openfda. Convenient access to the OpenFDA API

data-science-examples. A collection of data science examples implemented across a variety of languages and libraries.

data.table. R's data.table package extends data.frame:

R.utils. 🔧 R package: R.utils (this is *not* the utils package that comes with R itself)

cran.stats. Explore and visualise package download stats from Rstudio mirror by accounting for downloads from dependent packages

benchm-databases. A minimal benchmark of various tools (statistical software, databases etc.) for working with tabular data of moderately large sizes (interactive data analysis).

big.data.table. Distributed parallel computing on data.table

covr. Test coverage reports for R

plotly.js. Open-source JavaScript charting library behind Plotly and Dash

BuildingMachineLearningSystemsWithPython. Source Code for the book Building Machine Learning Systems with Python

sparkling-water. Sparkling Water provides H2O functionality inside Spark cluster

h2o-3. H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

benchm-ml. A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

feather. Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow