Popular GitHub Repositories for Bike

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Estimate power output given GPS data of a bike ride.

Bike sharing systems are a new generation of traditional bike rentals where the whole process from membership, rental and return back has become automatic. Through these systems, users are able to easily rent a bike from a particular position and return back at another position. Currently, there are about over 500 bike-sharing programs around the world which is composed of over 500 thousand bicycles. Today, there exists great interest in these systems due to their important role in traffic, environmental and health issues. Apart from interesting real-world applications of bike sharing systems, the characteristics of data being generated by these systems make them attractive for the research. The goal here is to build an end-to-end regression task. Here the user will provide the data and the result will be given by the best performing hype

This project aims to develop a machine learning model that predicts the demand for bike sharing in a given location. By analyzing historical data on weather conditions, day of the week, and other factors, we aim to create a model that can accurately forecast the number of bikes that will be rented at different times.

This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

Time series forecasting on Citi Bike daily demand using an additive regression model (Facebook Prophet) and a convolutional neural network (WaveNet)

Find Your Stolen Bike Lah! With AICU, We Kena Spot Your Bicycle on Carousell One Shot ???

Developers of all skill levels get hands on with machine learning through a cloud based 3D racing simulator, fully autonomous 1/18th scale race car driven by reinforcement learning, and global racing league.

CABRA: Cost-aware Adaptive Bike Repositioning Agent using Deep Reinforcement Learning

Low power rear view camera system for cycling to perform people detection using Tensorflow Lite for Microcontrollers

This a repo for the projects I completed during my Deep Learning Udacity Nanodegree.

Predicting Bike Rental Usage by using Artificial Neural Networks (Regression task)

A multi-use helmet that tells you what is behind you using machine learning. This is a continuation of the TPU bike project.

This project leverages AutoGluon in AWS SageMaker Studio to predict bike sharing demand, automating model training and tuning for accurate forecasting.

In part-1 of this project, the task is to build an explainable ML model using H2o package on the bike rental dataset and display various plots and noting the insights. In part-2, the task is to build a docker container to perform batch serving of a ML model.

Project - Predict Bike Sharing using Python and MLFlow

This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

Bike trip analysis to convince investors that a bike-sharing program in Des Moines is a solid business proposal.

Machine learning project achieving 66% RMSE improvement in bike sharing demand prediction using AutoGluon, temporal feature engineering, and systematic hyperparameter optimization. Demonstrates iterative model development from baseline (1.32 RMSE) to optimized solution (0.45 RMSE).

预测自行车数据集的计数变量