Sourav Singh's repositories
mnist-adversarial-attack
adversarial-mnist
astroid
A common base representation of python source code for pylint and other projects
axelrod-feedstock
A conda-smithy repository for axelrod.
bioncd-hackseq
BIOlogical implementation of the Normalized Compression Distance
chainer
A flexible framework of neural networks for deep learning
chainercv
ChainerCV: a Library for Deep Learning in Computer Vision
dask
Parallel computing with task scheduling
dask-ml
Scalable Machine Learn with Dask
deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
djangogirl-blog
This a web log built following django girls tutorials.
fidgit
An ungodly union of GitHub and Figshare
gensim
Topic Modelling for Humans
gensim-feedstock
A conda-smithy repository for gensim.
imbalanced-learn
Python module to perform under sampling and over sampling with various techniques.
lanes_detection
Lanes Detection Presentation for UpCode Academy
LightGBM
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
models
Models and examples built with Chainer
Neurovault-Analysis
Code for project on large-scale neuroimaging analysis for system-level cognitive mapping
nilearn
Machine learning for NeuroImaging in Python
opsdroid
🤖 An open source chat-ops bot framework
probability
Probabilistic reasoning and statistical analysis in TensorFlow
project-template
A template for scikit-learn extensions
react-router-Switch-and-NavLink-Example
implementation of react-router switch and NavLink component
scikit-beam
Data analysis tools for X-Ray, Neutron and Electron sciences
smart_open-feedstock
A conda-smithy repository for smart_open.
Synopsis
Project Synopsis
Tumor-segmentation
Code for Brain Tumor Segementation
yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.