mwohlers

mwohlers's Stars

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python57.1k4581325.8k

• microsoft/AI-For-Beginners

  12 Weeks, 24 Lessons, AI for All!

  Language:Jupyter Notebook35.1k4121156k

• google-research/google-research

  Google Research

  Language:Jupyter Notebook34.5k7551.3k7.9k

• deepinsight/insightface

  State-of-the-art 2D and 3D Face Analysis Project

  Language:Python23.7k5132.5k5.4k

• NVlabs/instant-ngp

  Instant neural graphics primitives: lightning fast NeRF and more

  Language:Cuda16.1k2041k1.9k

• ABZ-Aaron/CheatSheets

  Just a place to store cheatsheets

  1.7k741274

• google/uncertainty-baselines

  High-quality implementations of standard and SOTA methods on a variety of tasks.

  Language:Python1.5k2289204

• kennethleungty/Llama-2-Open-Source-LLM-CPU-Inference

  Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A

  Language:Python9531424213

• vincentarelbundock/modelsummary

  Beautiful and customizable model summaries in R.

  Language:HTML9181070577

• maxjcohen/transformer

  Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

  Language:Jupyter Notebook8581559166

• fabsig/GPBoost

  Combining tree-boosting with Gaussian process and mixed effects models

  Language:C++5771312846

• yandex-research/rtdl-num-embeddings

  (NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning

  Language:Python31942233

• AtomScott/SportsLabKit

  A python package for turning sports video into csv files

  Language:Jupyter Notebook23462619

• izmailovpavel/understandingbdl

  Language:Jupyter Notebook23461438

• FootballAnalysis/footballanalysis

  Language:Python16741536

• aws-samples/amazon-sagemaker-feature-store-end-to-end-workshop

  Language:Jupyter Notebook130302649

• julianfaraway/rexamples

  worked R examples

  Language:Stan1144020

• facebookresearch/meta-ot

  Meta Optimal Transport

  Language:Python97636

• aruberts/TabTransformerTF

  TensorFlow implementation of TabTransformer

  Language:Jupyter Notebook794814

• ML4GLand/EUGENe

  Elucidating the Utility of Genomic Elements with Neural Nets

  Language:Jupyter Notebook654154

• tashapiro/30DayMapChallenge

  The official website for #30DayMapChallenge, It is a daily mapping/cartography/data visualization challenge aimed at the spatial community. Code for map submissions.

  Language:R47204

• ayulockin/DataAugmentationTF

  Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.

  Language:Jupyter Notebook352012

• gsimchoni/lmmnn

  Language:Jupyter Notebook29218

• databricks-industry-solutions/causal-incentive

  Accelerator for customer incentive investment using causal inference techniques

  Language:Jupyter Notebook23204

• ushareng/FT-Transformer---TensorFlow

  Language:Jupyter Notebook16100

• pbansal5/DeepMVI

  Language:Python14104

• pcsl-epfl/diffeomorphism

  Apply maximum-entropy diffeomorphisms to images

  Language:Python9401

• ptonner/phenom

  A hierarchical non-parametric microbial phenotype model

  Language:Jupyter Notebook6102

• sunyue-xfel/Comparing-End-to-End-Machine-Learning-Methods-for-Spectra-Classification

  Language:Jupyter Notebook4102

• tmgrgg/localvsglobaluncertainty

  Empirical analysis of recent stochastic gradient methods for approximate inference in Bayesian deep learning, including SWA-Gaussian, MultiSWAG, and deep ensembles. See report_localglobal.pdf.

  Language:Python2250