Human Activity Recognition Model for Classifying Various Activities performed in Daily Life
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Updated
Jun 10, 2024 - Jupyter Notebook
Human Activity Recognition Model for Classifying Various Activities performed in Daily Life
Repository for Assignment 1 of team KAR.ai. - Human Activity Recognition (HAR) with Decision trees and LLMs
Machine learning model that can identify different human activities like walking, sitting, and running using data from an accelerometer. (Mini-Project from the course Machine Learning Fall 2025)
LSC50 — multimodal Colombian Sign Language recognition over 50 signs across IMU, body/face/hand landmarks, and ViViT video pipelines.
Mini-Project Given during the Assignment 1 of ML Course of IITGN ES-335
This is a robust and efficient ML model for recognizing various human activities such as walking, sitting, and running using accelerometer data.
A human activity recognizer based on accelerometer data using a decision tree classifier and a feature extractor (TSFEL).
Test nbdev package
This repository contains the code for the Assignment-1 of the course ES 335: Machine Learning 2024 at IIT Gandhinagar taught by Prof. Nipun Batra.
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