neelsoumya

neelsoumya's Stars

• nomic-ai/gpt4all

  GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

  Language:C++71.2k6492k7.8k

• huggingface/datasets

  🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

  Language:Python19.4k2773k2.7k

• Mooler0410/LLMsPracticalGuide

  A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

  9.6k18717737

• distillpub/template

  This is the repository for the distill web framework

  Language:JavaScript8271398136

• threedworld-mit/tdw

  ThreeDWorld simulation environment

  Language:Python5092014575

• rstudio/tufte

  Tufte Styles for R Markdown Documents

  Language:R4012692110

• cvanwynsberghe/pyworld3

  The World3 model revisited in Python

  Language:Python30311631

• leeper/slopegraph

  Edward Tufte-Inspired Slopegraphs

  Language:R188142321

• mxbi/arckit

  Tools for working with the Abstraction & Reasoning Corpus

  Language:Python1655422

• SaturnCassini/gpt4all_generative_agents

  Generative Agents: Interactive Simulacra of Human Behavior using GPT4All free model which runs on CPU

  111378

• volotat/ARC-Game

  The Abstraction and Reasoning Corpus made into a web game

  Language:JavaScript86186

• ElliottDyson/OSGA

  Open-Source Generative Agents is a community-driven fork of 'Generative Agents,' aimed at enabling compatibility with open-source Large Language Models; enhancing performance and adaptability; and introducing new relevant (optional) features

  Language:Python5771311

• ibecav/CGPfunctions

  Powell Miscellaneous Functions for Teaching and Learning Statistics

  Language:R2722611

• acceleratescience/large-language-models

  Get an introduction to how large language models work, and how to get up and running quickly.

  Language:Jupyter Notebook243412

• carlhenrikek/COMS30115

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• georgetown-cset/eto-chip-explorer

  ETO Chip Explorer

  Language:JavaScript1722288

• coolvision/bongard-problems-cnn

  Language:C13305

• joannecheng/napoleon_analysis

  Analyzing the dimensions in Minard's graphic of Napoleon's Russian campaign

  Language:R9204

• nyoma-diamond/competitive_generative_agents

  Generative Agents: Interactive Simulacra of Human Behavior

  Language:Python91

• simonalford42/bidir-synth

  Language:Python5104

• coolvision/random_shapes_generator

  Language:C++4303

• cambiotraining/visual-data-communication

  A course to learn the basics on communicating data effectively, using visualisation.

  Language:Lua2332

• mlatcl/advds

  Advanced Data Science unit

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• neelsoumya/awards

  Awards (feel good folder) public

  Language:Shell120

• neelsoumya/complex_stories_explanations

  Complex stories as explanations for machine learning models

  Language:Jupyter Notebook1201

• neelsoumya/neelsoumya.github.io

  this is me!

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• neelsoumya/practical_supervised_machine_learning

  A practical in R for teaching supervised machine learning

  Language:R120

• neelsoumya/public_supervised_machine_learning

  A lecture on supervised machine learning

  Language:Shell120

• neelsoumya/visualization_lecture

  visualization lecture

  Language:R1201

• WadhwaniAI/tb-disease-modelling

  Repository for code and experiments for Wadhwani AI's efforts on TB disease modelling, in partnership with Prof Nim. Final aim is to get accurate burden estimates for districts pan-India

  Language:Jupyter Notebook1001