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scikit-plot

An intuitive library to add plotting functionality to scikit-learn objects.

scipy-2018-sklearn

Scipy 2017 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller

scipy2017_simplecomputationalstats_tutorial

scipy2018-jupyterlab-tutorial

Tutorial material and instruction for scipy 2018 jupyterlab tutorial

scrapy-web-crawler-by-rest-api

Example Scrapy project to crawl the web using the site's REST API

search-engine-optimization

:mag: A helpful checklist / collection of Search Engine Optimization (SEO) tips and techniques.

self-driving-car

Udacity Self-Driving Car Engineer Nanodegree projects.

self-driving-toy-car

A self driving toy car using end-to-end learning

self_drive

基于树莓派的自动驾驶小车，利用树莓派和tensorflow实现小车在赛道的自动驾驶。（Self-driving car based on raspberry pie（tensorflow））

sematch

semantic similarity framework for knowledge graph

seq2seq-signal-prediction

Signal prediction with a seq2seq RNN model in TensorFlow

seq2seqchatbots

Seq2seq chatbot models, check paper link

shinyapps

Small web apps that illustrate statistical concepts

shopify-scraper

Simple scraper to extract all products from shopify sites

sicp-pdf

SICP PDF with Texinfo and LaTeX source

skater

Python Library for Model Agnostic Interpretation

sketchify

turn svg graph into sketchy visualization

sklearn-deap

Use evolutionary algorithms instead of gridsearch in scikit-learn

sklearn_tutorial

Materials for my scikit-learn tutorial

smartyoutubetv

Watch YouTube videos on your TV and set-top-box with comfort

snownlp

Python library for processing Chinese text

sorcery

Dark magic delights in Python

sotawhat

Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.

spark-deep-learning

Deep Learning Pipelines for Apache Spark

speech-language-processing

A curated list of speech and natural language processing resources

springboard

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

starter-slapp-app

state-of-the-art-result-for-machine-learning-problems

This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.

stats337

Readings in applied data science