mohitsharma29

mohitsharma29'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:Python52.1k4361305.4k

• soulmachine/machine-learning-cheat-sheet

  Classical equations and diagrams in machine learning

  Language:TeX6.6k379151.2k

• probml/pyprobml

  Python code for "Probabilistic Machine learning" book by Kevin Murphy

  Language:Jupyter Notebook6.4k1914541.5k

• sshkhr/awesome-mlss

  🤖 Machine Learning Summer School deadlines

  Language:JavaScript2.6k27232295

• gerdm/prml

  Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

  Language:Jupyter Notebook2k320473

• rmcelreath/statrethinking_winter2019

  Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019

  2k17336392

• michaelgutmann/ml-pen-and-paper-exercises

  Pen and paper exercises in machine learning

  Language:TeX1.8k303136

• jacobhilton/deep_learning_curriculum

  Language model alignment-focused deep learning curriculum

  1.2k17196

• kuleshov/cornell-cs5785-2020-applied-ml

  Teaching materials for the applied machine learning course at Cornell Tech (online edition)

  Language:Jupyter Notebook872202236

• tim-learn/awesome-test-time-adaptation

  Collection of awesome test-time (domain/batch/instance) adaptation methods

  60917144

• sebastian-hofstaetter/teaching

  Open-Source Information Retrieval Courses @ TU Wien

  Language:Python582181985

• craffel/dl3d-seminar

  Course webpage for COMP 790, (Deep) Learning from Limited Labeled Data

  30123028

• deeppavlov/tdl

  Course "Theories of Deep Learning"

  Language:Jupyter Notebook19522025

• probabilisticai/probai-2022

  Materials of the Nordic Probabilistic AI School 2022.

  Language:Jupyter Notebook1716028

• dobriban/Topics-In-Modern-Statistical-Learning

  Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc

  1564014

• pmichaillat/math-for-macro

  Source files of the course "Mathematics for Macroeconomics"

  Language:TeX1317045

• glouppe/info8004-advanced-machine-learning

  Lectures for INFO8004 Advanced Machine Learning, ULiège

  Language:CSS10112028

• pmichaillat/intermediate-macro

  Source files of the course "Intermediate Macroeconomics"

  977028

• yongkaiwu/FairAI

  This is a collection of papers and other resources related to fairness.

  Language:HTML919019

• s-nlp/annotated-transformer

  http://nlp.seas.harvard.edu/2018/04/03/attention.html

  Language:Jupyter Notebook62100

• niaohe/Convex-Optimization-Course

  Repository for my convex optimization course.

  503019

• stanleyn/Comp790-166-Comp-Bio

  Computational Biology- Spring 2021

  Language:TeX45306

• niaohe/Big-Data-Optimization-Course

  Repository for my Big Data Optimization course

  311015

• PredictiveIntelligenceLab/TRIPODS_Winter_School_2022

  Practicum on Supervised Learning in Function Spaces

  Language:Jupyter Notebook305010

• solevillar/Inference_and_Representation

  Language:TeX22607

• mltheory/CS7545

  Language:TeX17307

• fabianp/DSOML_2017

  Language:Jupyter Notebook123

• xAlpharax/NeuralODE-Notes-Projects

  Repository for notes, projects and snippets on NODEs. Includes results after training CNN based networks with different methods on MNIST, CIFAR-10, CelebA and CatsAndDogs datasets accordingly.

  Language:Python10500

• xycheng/minicourse-kernel-method

  Mini-course taught at Duke 2021 Fall

  4

• helloworld/cmsc498final

  Language:Jupyter Notebook2210