prediction

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

List of papers, code and experiments using deep learning for time series forecasting

🐗 🐻 Deep Learning based Python Library for Stock Market Prediction and Modelling

A high-level machine learning and deep learning library for the PHP language.

A neural network library built in JavaScript

Machine Learning Platform and Recommendation Engine built on Kubernetes

MLBox is a powerful Automated Machine Learning python library.

Header-only library for using Keras (TensorFlow) models in C++.

RNN based Time-series Anomaly detector model implemented in Pytorch.

Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University

🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained

🚘 "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.

Deep neural network framework for multi-label text classification

Real-time object detection on Android using the YOLO network with TensorFlow

Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.

Introducing neural networks to predict stock prices

This repository helps you understand python from the scratch.

Deep learning time series prediction with TensorFlow - TFTS

Fast webpages for all browsers.

Estimated Marginal Means and Marginal Effects from Regression Models for ggplot2

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）.

Tool that predicts the outcome of a Dota 2 game using Machine Learning

Regression, Scrapers, and Visualization

Curated Tensorflow code resources to help you get started with Deep Learning.

Mathematica implementations of machine learning algorithms used for prediction and personalization.

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series