There are 40 repositories under prediction topic.
Statsmodels: statistical modeling and econometrics in Python
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
NeuralProphet: A simple forecasting package
List of papers, code and experiments using deep learning for time series forecasting
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
MLBox is a powerful Automated Machine Learning python library.
Machine Learning Platform and Recommendation Engine built on Kubernetes
RNN based Time-series Anomaly detector model implemented in Pytorch.
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
This repository helps you understand python from the scratch.
A lightweight header-only library for using Keras (TensorFlow) models in C++.
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
A flexible, high-performance carrier for machine learning models(『飞桨』服务化部署框架)
:oncoming_automobile: "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
tfts: Time Series Deep Learning Models in TensorFlow
Introducing neural networks to predict stock prices
Deep neural network framework for multi-label text classification
Real-time object detection on Android using the YOLO network with TensorFlow
Leetcode Rating Predictor built with Node. Browser extension and web interface.
Estimated Marginal Means and Marginal Effects from Regression Models for ggplot2
Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.
Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"
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).
Fast webpages for all browsers.
Regression, Scrapers, and Visualization
Predict time-series with one line of code.
Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.
Tool that predicts the outcome of a Dota 2 game using Machine Learning
Mathematica implementations of machine learning algorithms used for prediction and personalization.