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spatio-temporal-paper-list

Spatio-temporal modeling 论文列表（主要是graph convolution相关)

spearmint

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012

spherical-cnn

Demo code for the paper "Learning SO(3) Equivariant Representations with Spherical CNNs"

spug

开源运维平台：帮助中小型企业完成主机、任务、发布部署、配置文件、监控、报警等管理(open source O & M management system,manage the hosts, tasks, deployment, configuration files, monitoring and alarming) https://spug.qbangmang.com/login

squad

Building QA system for Stanford Question Answering Dataset

sr-behavioral-fitting-

fits rl models to revluation scores/index

srsa

R Package for Successor Representation Scanpath Analysis

ssah

Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval(CVPR2018)

sta663-2015

Course materials for STA663

stackgan-pytorch

starcraft

This project creates a bridge between BWAPI for StarCraft: Brood War and EIS-enabled Multi-Agent Systems like GOAL.

starcraft-ai

Reinforcement Learning and Transfer Learning based StarCraft Micromanagement

stat-cookbook

The probability and statistics cookbook

stat212b

Topics Course on Deep Learning UC Berkeley

stereo_slam

stgcn_ijcai-18

Spatio-Temporal Graph Convolutional Networks

stochastic_depth

Code for Deep Networks with Stochastic Depth

stochastic_value_gradient

Implementation of (Learning Continuous Control Policies by Stochastic Value Gradients)[https://arxiv.org/abs/1510.09142]

stock

雪球股票讨论度与价格走势的关系

stock-1

30天掌握量化交易 (持续更新)

stock-patterns-explorer

Discovery of stock market patterns using association rules.

stock-predictor

Listens for Stock news on Twitter, performs sentiment analysis by mining information from an online news source, performs supervised predictive modeling and suggests buy or sell decisions of the stock. Computes portfolio returns over time.

stock-rnn

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

stock-selection-a-framework

This project demonstrates how to apply machine learning algorithms to distinguish "good" stocks from the "bad" stocks.

stock2vec

Embedding stocks to vectors based on the price history

stockholm

一个股票数据（沪深）爬虫和选股策略测试框架

stockpatternrecognition

NYU DS-GA-1003 Machine Learning Final Project

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

stocks-pattern-analyzer

This tool should help discover different patterns based on similarity measures in historical (financial) data

stocksight

Stock analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis