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Valles Marineris Hiker's Projects

spellcorrect icon spellcorrect

A program to correct non-word spelling error in sentences using ngram MAP Language Models, Noisy Channel Model, Error Confusion Matrix and Damerau-Levenshtein Edit Distance.

stanford_alpaca icon stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

stanfordnlp icon stanfordnlp

Official Stanford NLP Python Library for Many Human Languages

stock icon stock

股价预测程序,尝试各种模型。

stock-1 icon stock-1

stock,股票系统。使用python进行开发。

stock-api icon stock-api

股票接口 | 韭菜小猪 | A股 | 美股 | 港股 | 股票 | 基金 | JavaScript

stock-app icon stock-app

这是一款股票类Android APP软件主要实现了四个功能:1、财经咨询查看功能。2、大盘指数及各股市股票详细信息查看功能。3、股票交易计算器功能。4、与自建的模拟服务器交互,实现预测第二天股票“开高低收”功能和自动判断股票交易时机的功能等

stock-app-1 icon stock-app-1

Android 股票app 系统,做股票行情相关开发。

stock-market-prediction icon stock-market-prediction

We propose a stock market recommender system that analyses stock data and suggests a ranked basket of stocks. The objective of this recommender system is to support stock market traders, individual investors and fund managers in their decisions. Recommender systems apply different techniques of data mining on data and find similarities among various data items using live prices, historical data and news articles.

stock-market-prediction-using-natural-language-processing icon stock-market-prediction-using-natural-language-processing

We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a model that will be able to buy and sell stock based on profitable prediction, without any human interactions. The model uses Natural Language Processing (NLP) to make smart “decisions” based on current affairs, article, etc. With NLP and the basic rule of probability, our goal is to increases the accuracy of the stock predictions.

stock-price-prediction icon stock-price-prediction

Stock price prediction using LSTM and 1D Convoltional Layer implemented in keras with TF backend on daily closing price of S&P 500 data from Jan 2000 to Aug 2016

stock-serverbuilding icon stock-serverbuilding

自建的模拟服务器:主要用于后台运行股票预测模型,目前主要实现当客户端发送请求时将股票模型运行的结果返回给APP端(即预测第二天股票的开高低收的涨跌趋势并返回给客户端和自动判断股票买卖时机的功能)

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