eagleye3192's Stars
Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
GokuMohandas/Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
ossu/data-science
📊 Path to a free self-taught education in Data Science!
ml-tooling/best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
zziz/pwc
This repository is no longer maintained.
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
stanfordnlp/stanza
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
geocompx/geocompr
Geocomputation with R: an open source book
lennardv2/Leaflet.awesome-markers
Colorful, iconic & retina-proof markers for Leaflet, based on the Font Awesome/Twitter Bootstrap icons.
lindawangg/COVID-Net
COVID-Net Open Source Initiative
satinder147/DeepWay
This project is an aid to the blind. Till date there has been no technological advancement in the way the blind navigate. So I have used deep learning particularly convolutional neural networks so that they can navigate through the streets.
yindeng/shinyData
A GUI for interactive data analysis, visualization and presentation
abdulfatir/sampling-methods-numpy
This repository contains implementations of some basic sampling methods in numpy.
AlexSWong/COVID-Net
Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global multi-disciplinary team of researchers, developers, and clinicians have made publicly available a suite of tailored deep neural network models for tackling different challenges ranging from screening to risk stratification to treatment planning for patients with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, we have made available fully curated, open access benchmark datasets comprised of some of the largest, most diverse patient cohorts from around the world.