KevinSC13's repositories

blogScripts

Repository for code used in my blog posts

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fancyss

fancyss is a project providing tools to across the GFW on asuswrt/merlin based router.

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fancyss_history_package

科学上网插件的离线安装包储存在这里

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FBP

FBP项目全称FootBallPrediction,历经9个月完成的足球比赛预测项目。项目结合大数据+机器学习,不断摸索开发了一个程序。程序根据各大博彩公司赔率多维度预测足球比赛结果(包含胜和不胜)。机器学习用的是自己建立的“三木板模型”算法,已在国家期刊发表论文并被万方数据库收录,详见_ML_文件。目前准确率可达80%。该项目在自己创建的微信群里已经吸引了很多人,附件为群讨论截图,并且每天均有部分人根据预测结果参考投注竞彩,参考的人都获得了相应的收益。 现在想通过认识更多的有识之士,一起探索如何将项目做大做强,找到合伙人,实现共赢。希望感兴趣的同仁联系本人,微信号acredjb。公众号AI金胆(或AI-FBP),每天都有程序预测的足球比赛。程序优势请看Advantages和README文件。程序3.0版本:(第三轮目前13中12) 8月10日:13让负(正确) 8月11日:27让负(正确) 8月12日:11让负(正确) 8月13日:6胜(不正确) 8月14日:25让负(正确) 8月15日:无预测 8月16日:1胜(正确) 8月17日:6让负(正确) 8月18日:16胜(正确) 8月19日:34让负(正确) ... 1.0版本(第一轮为11中9) 2.0版本(第二轮13中11).

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fifa-FUT-Data

Web-scraping script that writes the data of all players from FutHead and FutBin to a CSV file or a DB

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football-predictor

Using a Deep Neural Network (DNN) to predict the results of Premier League Football Matches

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Pandas-Cookbook-Second-Edition

Pandas Cookbook Second Edition, published by Packt

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pgmpy

Python Library for Probabilistic Graphical Models

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pgmpy_notebook

Short Tutorial to Probabilistic Graphical Models(PGM) and pgmpy

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Predicting_Winning_Teams

This is the code for "Predicting the Winning Team with Machine Learning" by Siraj Raval on Youtube

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ProphitBet-Soccer-Bets-Predictor

ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.

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soccerdata

⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, SoFIFA, Understat and WhoScored.

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sports_betting_with_reinforcement_learning

This is the code for "Sports Betting with Reinforcement Learning" By Siraj Raval on Youtube

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ThinkBayes2

Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

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ThinkStats2

Text and supporting code for Think Stats, 2nd Edition

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