abhi25t

abhi25t's Stars

• d2l-ai/d2l-en

  Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

  Language:Python24.4k4202964.4k

• facebook/prophet

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

  Language:Python18.7k4532.2k4.6k

• onnx/onnx

  Open standard for machine learning interoperability

  Language:Python18.2k4372.9k3.7k

• alievk/avatarify-python

  Avatars for Zoom, Skype and other video-conferencing apps.

  Language:Python16.3k3266364.2k

• qubvel-org/segmentation_models.pytorch

  Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

  Language:Python9.9k836621.7k

• IntelRealSense/librealsense

  Intel® RealSense™ SDK

  Language:C++7.7k2889.6k4.8k

• google/flax

  Flax is a neural network library for JAX that is designed for flexibility.

  Language:Jupyter Notebook6.2k86936659

• thunil/TecoGAN

  This repo contains source code and materials for the TEmporally COherent GAN SIGGRAPH project.

  Language:Python6k1831231.1k

• beamandrew/medical-data

  5.8k336211.1k

• rmcelreath/stat_rethinking_2022

  Statistical Rethinking course winter 2022

  Language:R4.1k22422444

• MAIF/shapash

  🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

  Language:Jupyter Notebook2.8k37220334

• rmcelreath/rethinking

  Statistical Rethinking course and book package

  Language:R2.2k113373606

• rmcelreath/statrethinking_winter2019

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

  2k17436392

• yassouali/pytorch-segmentation

  :art: Semantic segmentation models, datasets and losses implemented in PyTorch.

  Language:Jupyter Notebook1.7k22145386

• enjalot/algovis

  collection of projects and links about algorithm visualization

  1.7k8616117

• sawcordwell/pymdptoolbox

  Markov Decision Process (MDP) Toolbox for Python

  Language:Python5302427252

• echonet/dynamic

  EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.

  Language:Python4832758169

• poets-ai/elegy

  A High Level API for Deep Learning in JAX

  Language:Python4711610632

• icoxfog417/awesome-financial-nlp

  Researches for Natural Language Processing for Financial Domain

  40621063

• allenai/naacl2021-longdoc-tutorial

  Language:Python34411236

• facebookresearch/differentiable-robot-model

  We are implementing differentiable models of robot manipulators, which allows us to learn typically assumed to be known models of robots for control and motion planning.

  Language:Python240131337

• gbosquechacon/statrethink_course_in_pymc3

  Statistical Rethinking course in pymc3

  Language:Jupyter Notebook14210444

• luisguiserrano/hmm

  An implementation of the Viterbi Algorithm for training Hidden Markov models. This repo accompanies the video found here: https://www.youtube.com/watch?v=kqSzLo9fenk

  Language:Jupyter Notebook1404269

• microsoft/petridishnn

  Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search

  Language:Python11014222

• marshuang80/penet

  Language:Python464423

• lafith/pymusica

  A contrast enhancement approach involving non linear mapping of Laplacian pyramid.

  Language:Python20125

• braindotai/Deep-Learning-Scratch-Arena

  Implementing most important basic building blocks of Deep Learning from scratch. My goal is to provide high quality Scratch Implementations of the fundamentals of Deep Learning and its applications, with interactive well documentated jupyter notebooks. All notebooks come along with implementations using Tensorflow, MXNet and Pytorch.

  Language:Jupyter Notebook17203

• elisa-aleman/MeCab-python

  Example usage of the python wrappers for MeCab Japanese parser in MacOSX.

  Language:Python9100

• karthikchiru12/Algovis

  Algovis, a simple way of learning algorithms through visualizations

  Language:JavaScript9344

• pemagrg1/Japanese-NLP

  Japanese NLP. Created Date: 17 July 2019

  Language:Python5301