kventinel

kventinel's Stars

• pytorch/pytorch

  Tensors and Dynamic neural networks in Python with strong GPU acceleration

  Language:Python84.2k1.7k46.7k22.7k

• google/jax

  Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

  Language:Python30k3285.5k2.7k

• ycm-core/YouCompleteMe

  A code-completion engine for Vim

  Language:Python25.5k5583.2k2.8k

• fivethirtyeight/data

  Data and code behind the articles and graphics at FiveThirtyEight

  Language:Jupyter Notebook16.9k1.3k16210.9k

• fatih/vim-go

  Go development plugin for Vim

  Language:Vim Script16k2622k1.4k

• ranaroussi/yfinance

  Download market data from Yahoo! Finance's API

  Language:Python14.9k2421.4k2.4k

• LonamiWebs/Telethon

  Pure Python 3 MTProto API Telegram client library, for bots too!

  Language:Python10k1562.3k1.4k

• yandexdataschool/nlp_course

  YSDA course in Natural Language Processing

  Language:Jupyter Notebook9.8k364462.6k

• yandexdataschool/Practical_RL

  A course in reinforcement learning in the wild

  Language:Jupyter Notebook5.9k2091861.7k

• MattPD/cpplinks

  A categorized list of C++ resources.

  4.6k26111484

• facebookresearch/denoiser

  Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

  Language:Python1.7k36149302

• yandexdataschool/Practical_DL

  DL course co-developed by YSDA, HSE and Skoltech

  Language:Jupyter Notebook1.6k7018642

• python273/vk_api

  Модуль для создания скриптов для ВКонтакте | vk.com API wrapper

  Language:Python1.3k69344325

• ARM-software/armnn

  Arm NN ML Software. The code here is a read-only mirror of https://review.mlplatform.org/admin/repos/ml/armnn

  Language:C++1.2k90752313

• DmitryRyumin/INTERSPEECH-2023-24-Papers

  INTERSPEECH 2023-2024 Papers: A complete collection of influential and exciting research papers from the INTERSPEECH 2023-24 conference. Explore the latest advances in speech and language processing. Code included. Star the repository to support the advancement of speech technology!

  64288442

• lucidrains/conformer

  Implementation of the convolutional module from the Conformer paper, for use in Transformers

  Language:Python36691255

• yandexdataschool/sdc_course

  Short course about self-driving cars

  Language:JavaScript15739061

• Drapegnik/bsu

  🎓Repository for university labs on FAMCS, BSU

  Language:Java1042337

• Nikolay-Lysenko/readingbricks

  A structured collection of notes (mostly, on machine learning) and a Flask app for reading and searching them.

  Language:Jupyter Notebook939011

• inncaps/CodingHackathons

  It will contain the problems and solutions in one or more languages for the Past Coding Hackathons

  Language:Java722627

• gakarak/Yandex_SHAD_2017_Minsk_Seminars

  Yandex Shad 2017 code examples for seminar (Minsk)

  Language:Python5201

• yandexdataschool/mlhep-course-2017

  materials for course on machine learning for HEP at YSDA

  Language:Jupyter Notebook51303

• gw/xv6

  Language:C2306