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spotlight

Deep recommender models using PyTorch.

spring-cloud-alibaba

Spring Cloud Alibaba provides a one-stop solution for application development for the distributed solutions of Alibaba middleware.

sptag

A distributed approximate nearest neighborhood search (ANN) library which provides a high quality vector index build, search and distributed online serving toolkits for large scale vector search scenario.

spyder-notebook

Jupyter notebook integration with Spyder

sqlitedict

Persistent dict, backed by sqlite3 and pickle, multithread-safe.

sqlmap

Automatic SQL injection and database takeover tool

squeezenet

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters

squeezenet-deep-compression

squeezenet-generator

SqueezeNet Generator

squoosh

Make images smaller using best-in-class codecs, right in the browser.

srgan

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

ssgan-tensorflow

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

ssrfmap

Automatic SSRF fuzzer and exploitation tool

sta-663-2016

STA663 Statistical Computing and Computation, Spring 2016

sta-663-2017

Notebooks, worksheets and homework for STA 663 class

sta-663-2018

stackoverflow-py-top-qa

stackoverflow上Python相关回答整理翻译

staged-recipes

A place to submit conda recipes before they become fully fledged conda-forge feedstocks

stanford-cs-229-cn

A Chinese Translation of Stanford CS229 notes 斯坦福机器学习CS229课程讲义的中文翻译

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

stanford-machine-learning-course

machine learning course programming exercise

stanford-tensorflow-tutorials

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

stanza

Stanford NLP group's shared Python tools.

starlette

The little ASGI framework that shines. ✨

stat302

notes from my 302 class on Bayesian methods and principles of statistics

stat479-deep-learning-ss19

Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison

stat479-machine-learning-fs19

Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison

statistical-rethinking

Notebooks containing R code from Richard McElreath's Statistical Rethinking

statistical-rethinking-with-python-and-pymc3

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath