We propose an exercises recommendation algorithm which uses model-free reinforcement learning with neural network function approximation to learn an exercise recommendation policy. The policy directly operates on raw observations of a student's exercise history.

A personalized exercise recommendation system using collaborative filtering and ML models like SVD, ALS, and KNN. An interactive Streamlit dashboard for exploring and visualizing data-driven fitness suggestions.

Jun 1, 2024 · In this study, we aim to propose an exercise recommendation paradigm that can reveal the latent connections between student-student (exercise-exercise). Specifically, a new framework was proposed, namely personalized exercise recommendation with student and exercise portraits (PERP).

In this paper, we propose an exercise recommendation system that also predicts individual success rates. The system, consisting of two inter-connected recurrent neural networks (RNNs), uses the history of workouts to recommend the next workout activity for each individual.

Objective: Integrate exercise data with FMS assessment results to create a personalized and safe exercise recommendation system. Steps: Data Integration: Combine exercise attributes with FMS suitability ratings (green/yellow/red). Data Preprocessing: Encode, normalize, and handle missing values in the dataset.

Sep 16, 2024 · With the advent of technology, we have the tools to make fitness more accessible and personalized. This article delves into the creation of an AI-powered exercise recommendation system,...

To address these limitations, we employ graph neural networks (GNNs) to learn node representations in exercise recommendation contexts and propose a new knowledge tracing-enhanced multitask exercise recommendation framework, called MLKT4Rec.

Jan 1, 2018 · Intelligent exercise recommendation is a research focus in the field of online learning that can help learners quickly find exercises suitable for them from the exercise bank. However, exercise recommendation differs from product or film recommendation because of some special requirements.

Nov 12, 2024 · This paper introduces a novel exercise recommendation system that utilizes reinforcement learning to personalize walking exercises based on the user’s biomarkers and context, aiming to improve the user’s aerobic capacity significantly.

eeds, adversely affecting their learning efficiency and outcomes. To address these challenges, this paper proposes an exercise recommendation algorithm that combines the emerging fields of reinforcement learning and recomme. dation systems to help learners find suitable exercise resources. Initially, we use a knowledge t.