The Project is mainly focused on Parkinson's detection using the machine learning models and obtaining the accuracies of the test and train values of the dataset.
It is an AI powered text promoter that will allow users to check for spellings, grammar, vocabulary, see writing prompts and summarize to para or points based on user command.
This project focuses on building a model for the detection of epilepsy using EEG signals. Epilepsy is a neurological disorder that affects millions of people worldwide. The detection of epilepsy and changes in mental state is important for the diagnosis using DL/ML algorithms.
Intel oneAPI Based Emotion Recognition�using NLP (Audio & Text)
Human-Computer interactions are make it mandatory to get accuracy communications, like both human. If computer identify means we will get clever interaction so NLP based recognition gives better accuracy.
The machine learning project aims to implement machine learning algorithms to detect whether a person in a given image is wearing a mask or not.The algorithm used in this project is Convolutional Neural Network (CNN) which is a well known algorithm for image classification.
This project detects forest cover and the barren land in a specific area and predicts soil and temperature in that specific area(barren land) and recommends the tree which can thrive at that environment.
The drowsiness detection system monitors the driver's condition and issues an alert if it detects signs of drowsiness using CNN - Python, OpenCV.
This system aims to reduce the number of accidents on the road by detecting the driver's drowsiness and warning them using an alarm.
The project aims to provide properties based on the Habitability Index for people finding properties to rent. This Habitability index is found by an ML model that's backed by oneAPI.
Farmers are experiencing significant crop loss due to ineffective weed management, which results in decreased yield, increased costs, and environmental harm. Current weed detection methods are time-consuming, unreliable, and require manual labor. The lack of efficient weed management solutions resul
Image classification for recycling refers to the use of machine learning to automatically classify images of waste materials into their respective categories. We have made use of Intel's oneAPI and its oneDNN library which provides highly optimized routines for various deep learning operations.
We aim to create an accurate and efficient model that can determine fresh water quality based on various factors such as source, location, season, etc. The repository contains the code and data used in the development of the model, as well as the results and findings of the project.
OMPify is a tool for creating a comprehensive database that contains multiple modalities of code, including source code, AST format, etc. Using this database, OMPify can be used to train large language models, allowing them to learn the semantics of code and generate OpenMP pragmas automatically.
Hello everyone this project is about chatbot using Python programming
The project aims to develop a chatbot AI using Python programming language. The chatbot will be designed to interact with users in natural language
The main aim of the data is to differentiate healthy people from those with PD, according to the "status" column which is set to 0 for healthy and 1 for PD.(PD stands for Parkinson's Disease)
The entire implementation has been carried out with the intel oneAPI. A logistic regression model to identify correlations between the following 9 independent variables and the class of the tumour (benign or malignant).
a. Clump thickness b. Uniformity of cell size c. Uniformity of cell shape. Mar