This project is designed to predict the likelihood of a person developing diabetes based on a number of risk factors. The goal of tproject is to help identify individuals who are at high risk for the disease so that preventive measures can be taken early on to minimize the likelihood of complication
A comprehensive algorithm that generates a brief summary of a given research paper.Paper summarization is a crucial tool that helps researchers, students, and professionals save time and effort when working with research papers. However, summarizing research papers can be a daunting task, especially
US lenders use AI to understand mortgage delinquency risks, but models must be updated with changing data to remain accurate. Fair predictions are essential for ethical AI and building trust in AI systems impacting society.
We aim to create an intelligent system that can recommend personalized diets for individuals based on specific parameters like age,type of diet(vegan/non-vegan),weight and height. The system will use machine learning algorithms to analyze these parameters to generate a diet plan.
Obesity is a global health concern that is associated with various health problems. To address this issue, we propose a machine learning-based tool that predicts a person's health status based on their obesity level, which is determined using their height and weight.
Bengaluru House Prediction is an ML model with a user-friendly Flask interface built using Intel One API. It predicts home prices using pandas, scikit-learn, and matplotlib. The project benefits homebuyers, agents, and developers, demonstrating data science's power.
This project involves identifying edible mushrooms using various features such as cap shape, cap color, gill size, spore print color, habitat, and other characteristics.
OneDAL library project to build and optimize machine learning models for predicting the price of diamonds based on their various characteristics such as carat, cut, color, clarity, depth, and table.
Air wiggle ; Project submission on https://devmesh.intel.com/
for the Learned worth consult digital technology company incoporated in Nigeria, cac no ; BN 3701056
https://www.github.com/free2ride19/air-wiggler
https://www.github.com/caseg-network/air-wiggler
Air wiggle aims to be a project
This project uses YOLO object detection to identify and remove weeds in agriculture. It offers an efficient, sustainable alternative to traditional pesticide-based weed management, resulting in increased yields. This system can automate weed detection and remediation, making it useful for farmers.
The project is based on one of the themes Intel® oneAPI Hackathon for Open Innovation. It aims to devise a Machine Learning tool to predict the quality of freshwater