Himanshu
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User Activity Recognition Model

The proposed system aims to predict the activity of humans by using Logistic Regression. This will help in recording the activity of athlete as well as facilitate the interaction between Humans and Computers. A brief overview of the functions is:
⦁ Exploring and cleaning the given data i.e., visualizing, dealing with null values, outliers, etc.
⦁ Applying a Logistic Regression algorithm to predict the activity based on the training data.
⦁ Getting rapid result by only selecting some of the important features that affect the prediction more.
Check it out here : https://colab.research.google.com/drive/1vYeaykIwtcBYjrJSo-_tqoFJkD6IcbRe

Problem Statement

Fitness and Sports

One area that has resonated greatly with activity recognition lately is sports, especially fitness and running. There are countless examples, in which the athlete or sportsperson is required to track his/her activity for selecting the next step in Training. But issues persist in the task to record his/her activity

Human – Computer Interaction

People’s pleasure in tendency and to play never disappears, and there have been many improvements in the gaming area. But the problem is that humans cannot interact with the computers physically to get most of the entertainment of computer games. Only by recognizing the activities a user is performing, the computer can understand the user and give a response based on human reactions. This way, the human–computer interaction is possible.

Installation

git clone https://github.com/himanshu010/human-activity-recognition.git
cd human-activity-recognition
pip install -r requirements.txt

Finally to run, navigate & open Logistic regression.ipynb file in jupyter notebook:

Screenshots

© Himanshu 2022.