nitinpaul

nitinpaul's Stars

• arwes/arwes

  Futuristic Sci-Fi UI Web Framework.

  Language:TypeScript7.1k292

• PacktPublishing/15-Math-Concepts-Every-Data-Scientist-Should-Know

  15 Math Concepts Every Data Scientist Should Know, published by Packt

  Language:Jupyter Notebook2114

• ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

  500 AI Machine learning Deep learning Computer vision NLP Projects with code

  20k5.1k

• leimao/PyTorch-Pruning-Example

  PyTorch Pruning Example

  Language:Python4614

• VainF/Torch-Pruning

  [CVPR 2023] DepGraph: Towards Any Structural Pruning

  Language:Python2.7k329

• andresvourakis/data-scientist-handbook

  This is a repo with links to everything you'd ever want to learn about data science

  61758

• facebookresearch/open_lth

  A repository in preparation for open-sourcing lottery ticket hypothesis code.

  Language:Python624113

• olegpolivin/pruningExperiments

  Repository to perform simple pruning experiments on neural networks

  Language:Jupyter Notebook186

• lecode-official/pytorch-lottery-ticket-hypothesis

  A PyTorch implementation of the Lottery Ticket algorithm introduced by Frankle et al. in "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" and enhanced by Zhou et al. in "Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask".

  Language:Python3

• rahulvigneswaran/Lottery-Ticket-Hypothesis-in-Pytorch

  This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.

  Language:Python32491

• kingabzpro/Annual-Recycled-Energy-Saved-in-Singapore

  Learn how much Singapore is saving energy per years by recycling plastics, paper, glass, ferrous and non-ferrous metal

  Language:Jupyter Notebook71

• rasbt/machine-learning-book

  Code Repository for Machine Learning with PyTorch and Scikit-Learn

  Language:Jupyter Notebook3.5k1.3k

• GreenAI-Uppa/pruningSPMM

  Language:Python63

• csyhhu/L-OBS

  Codes for Layer-wise Optimal Brain Surgeon

  Language:Python7518

• gunnarmorling/awesome-opensource-data-engineering

  An Awesome List of Open-Source Data Engineering Projects

  2k336

• minar09/awesome-virtual-try-on

  A curated list of awesome research papers, projects, code, dataset, workshops etc. related to virtual try-on.

  2.2k268

• TA-Lib/ta-lib-python

  Python wrapper for TA-Lib (http://ta-lib.org/).

  Language:Cython9.6k1.8k

• quantopian/pyfolio

  Portfolio and risk analytics in Python

  Language:Jupyter Notebook5.7k1.8k

• microsoft/computervision-recipes

  Best Practices, code samples, and documentation for Computer Vision.

  Language:Jupyter Notebook9.5k1.2k

• home-assistant/core

  :house_with_garden: Open source home automation that puts local control and privacy first.

  Language:Python72.6k30.4k

• dansuh17/deep-supervised-hashing

  pytorch implementation of Deep Supervised Hashing

  Language:Python93

• sasakishun/research

  Language:Python1

• TreezzZ/DHN_PyTorch

  Source code for paper "Deep Hashing Network for Efficient Similarity Retrieval" on AAAI-2016

  Language:Python156

• lofar-astron/PiLL

  Pipeline for Lofar LBA

  Language:Python54

• pengsongyou/openscene

  [CVPR'23] OpenScene: 3D Scene Understanding with Open Vocabularies

  Language:Python64044

• fastai/fastai

  The fastai deep learning library

  Language:Jupyter Notebook26.2k7.6k

• ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network

  Tools to Design or Visualize Architecture of Neural Network

  4.4k575

• roboflow/supervision

  We write your reusable computer vision tools. 💜

  Language:Python23.6k1.8k

• shuaichaochao/HybridHash

  HybridHash: Hybrid Convolutional and Self-Attention Deep Hashing for Image Retrieval (ICMR 2024)

  Language:Python81

• swuxyj/DeepHash-pytorch

  Implementation of Some Deep Hash Algorithms, Including DPSH、DSH、DHN、HashNet、DSDH、DTSH、DFH、GreedyHash、CSQ.

  Language:Python492117