ShT3ch's Stars
basalovyurij/nlp-text-search
hertg/egpu-switcher
🖥🐧 Setup script for eGPUs in Linux (X.Org)
dair-ai/nlp_newsletter
📰Natural language processing (NLP) newsletter
igrishaev/dotfiles
My Emacs config and other unix stuff
MyLtYkRiTiK/ComputerVision_Tutorials_in_Russian
src-d/lapjv
Linear Assignmment Problem solver using Jonker-Volgenant algorithm - Python 3 native module.
zopefoundation/ZODB
Python object-oriented database
VKCOM/YouTokenToMe
Unsupervised text tokenizer focused on computational efficiency
graykode/nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
geoopt/geoopt
Riemannian Adaptive Optimization Methods with pytorch optim
floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
alexandra-chron/siatl
PyTorch source code of NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models"
pytorch/contrib
Implementations of ideas from recent papers
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
omarsar/nlp_overview
Overview of Modern Deep Learning Techniques Applied to Natural Language Processing
pytorch/ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
lspvic/jupyter_tensorboard
Start Tensorboard in Jupyter Notebook
FreeCAD/FreeCAD
This is the official source code of FreeCAD, a free and opensource multiplatform 3D parametric modeler.
amkatrutsa/optimization_course
A course on Optimization Methods
oval-group/mlogger
a lightweight and simple logger for Machine Learning
pytorchbearer/torchbearer
torchbearer: A model fitting library for PyTorch
IINemo/isanlp
Natural language processing tools for English and Russian (postagging, syntax parsing, SRL, NER, language detection etc.)
PrincetonML/SIF
sentence embedding by Smooth Inverse Frequency weighting scheme
jwieting/iclr2016
Python code for training all models in the ICLR paper, "Towards Universal Paraphrastic Sentence Embeddings". These models achieve strong performance on semantic similarity tasks without any training or tuning on the training data for those tasks. They also can produce features that are at least as discriminative as skip-thought vectors for semantic similarity tasks at a minimum. Moreover, this code can achieve state-of-the-art results on entailment and sentiment tasks.
facebookresearch/SentEval
A python tool for evaluating the quality of sentence embeddings.
kefirski/pytorch_NEG_loss
NEG loss implemented in pytorch
cemoody/topicsne
t-SNE experiments in pytorch
dennybritz/deeplearning-papernotes
Summaries and notes on Deep Learning research papers
ValeryTyumen/Skoltech-NLA-OPT-Project
ARTM implementation project for assignment at Skoltech uni
hunkim/deep_architecture_genealogy
Deep Learning Architecture Genealogy Project