nkaufie's Stars
junyanz/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
KupynOrest/DeblurGAN
Image Deblurring using Generative Adversarial Networks
cocodataset/cocoapi
COCO API - Dataset @ http://cocodataset.org/
nightrome/cocostuff
The official homepage of the COCO-Stuff dataset.
abreheret/PixelAnnotationTool
Annotate quickly images.
diegoalejogm/gans
Generative Adversarial Networks implemented in PyTorch and Tensorflow
tjwei/GANotebooks
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
DanAnastasyev/DeepNLP-Course
Deep NLP Course
PhilippeW83440/Coursera-AML3-Bayesian-Methods
Coursera, Advanced Machine Learning specialization, course 3: Bayesian Methods for Machine Learning
johaupt/bayesian_methods
Exercises on Bayesian methods for machine learning
GeoTecINIT/OpenData4OpenCities
2nd Open Data for Open Cities full day Workshop for AGILE 2018 Conference in Lund University, Sweden.
SandraMNE/ECMLChallenge2016
minikarma/geotalk
Онлайн-курс «Визуализация геоданных»
chuanconggao/PrefixSpan-py
The shortest yet efficient Python implementation of the sequential pattern mining algorithm PrefixSpan, closed sequential pattern mining algorithm BIDE, and generator sequential pattern mining algorithm FEAT.
GrammarViz2/grammarviz2_src
GrammarViz 2.0 public release:
DLSchool/deep-learning-school
Официальный репозиторий курса Deep Learning (2018-2021) от Deep Learning School при ФПМИ МФТИ
sarab96/ClusteringNeuralNetworks
Unsupervised clustering of patients using CNN with Deep Learning
sisinflab/recommenders
Recommender Systems algorithms implementations
jacobeisenstein/gt-nlp-class
Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"
dreddsa5dies/DataScienceContest
shark8me/Building_Probabilistic_Graphical_Models_in_Python
Source code for the book "Building Probabilistic Graphical Models in Python"
CyberPoint/libpgm
A library for creating and using probabilistic graphical models
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Kotlin/kotlin-interactive-shell
Kotlin Language Interactive Shell
qrmtutorial/qrm
qrm
Yorko/mlcourse.ai
Open Machine Learning Course
rushter/MLAlgorithms
Minimal and clean examples of machine learning algorithms implementations
unnati-xyz/intro-to-deep-learning-for-nlp
The repository contains code walkthroughs which introduces Deep Learning in the field of Natural Language Processing.
hse-aml/intro-to-dl
Resources for "Introduction to Deep Learning" course.
alexeyev/HSE-SPb-BigData-Python-Fall2016
Материалы к курсу по программированию и инструментам анализа данных, прочитанному в петербургском филиале НИУ ВШЭ осенью 2016 года