Get the most out of your training, scoring, algorithms and frameworks on Intel® architecture for Deep Learning and Artificial Intelligence.
URL: https://github.com/DakshDadhania/Intel-Unnati_BrainWaves
FashionVision: Revolutionizing Clothing Recognition with Intel's OpenVINO Optimization. Our CNN model achieves 94.5% accuracy on Fashion MNIST, while OpenVINO cuts inference time by 97%. Explore our streamlined fashion recognition solution now!
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URL: https://github.com/Sinda271/BirdSpeciesClassification
Bird species identification is a deep learning project based on OneAPI-Tensorflow. The data includes a total number of 1856 audio records split into 40 bird species.
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In this project I have done some Data Analytics on a data set.
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URL: https://github.com/Varun-Vi/intelunnati_Team_Qubit
Road safety is a major concern today. Deep Automated driving and vehicle safety systems need object detection. It is important that object detection be accurate overall and robust to weather and environmental conditions and run in real-time. As a consequence of this approach, they require image.
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URL: https://github.com/AdarshWase/OneAPI-Water-Quality-Competition
This project aims to predict water quality, a critical aspect of environmental and public health. Leveraging a comprehensive dataset and advanced machine learning techniques, we strive to provide valuable insights into the suitability of water for consumption.
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URL: https://github.com/Priyal19/Oxygenius
Project Summary: OxyGenius - Real-Time Tree Planting Predictor OxyGenius is an innovative project aimed at addressing the pressing issue of global warming by harnessing the power of machine learning and real-time environmental data. The project's primary objective is to predict the number of trees
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URL: https://github.com/harsh-ka/RemovingBiasFromModel.git
Real world models are always at risk of amplifying or replicating the real world bias such as gender discrimination or racial discrimination .We provide a in processing based method to removing gender bias from Model.
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URL: https://github.com/anna-sai-nikhil/Intel-oneapi-stresstracker
Created a mobile app powered by a TensorFlow NLP model trained on Reddit posts data to predict text stress levels, aiding users in managing their emotional well-being. Flutter is used for the app building, and REST API is hosted in PythonAnywhere
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URL: https://github.com/02shanks/Water-Quality_Prediction_Intel-oneAPI
This project leverages Intel OneAPI libraries to create a versatile water quality prediction model. It ensures safe drinking water, aids environmental monitoring, and enhances industrial processes by analyzing diverse data sources and features.
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URL: https://github.com/Utsabab/Intel-oneAPI-Student-Ambassador
Welcome to the English Premier League (EPL) Match Result Prediction Project! In this project, I have implemented three different classification algorithms - K-Nearest Neighbors (KNN), Naive Bayes, and DecisDecision Trees - to predict the outcomes of EPL matches.
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URL: https://github.com/apanda1001/Machine-Learning-using-oneAPI/blob/main/intel_oneapi.ipynb
Existing literature uses CNN techniques and multiple variations and derivatives of the same to detect and classify tumors. This project explores the opportunity to: Utilise oneAPI to analyse the available datasets Utilise oneAPI libraries to try and implement the current existing methods for tumor c
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URL: https://github.com/RAJAT-COD3/intel_one_API
Intel one Api
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URL: https://github.com/Harsha1309/One_API_Intel_Hackathon
Drishti, is a computer vision-based assistive navigation system designed address the challenges faced by the visually impaired. By leveraging Intel’s AI Analytics tool advanced computer vision algorithms and depth estimation techniques.
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URL: https://github.com/SparshRastogi/Intel-OneAPI
We have predicted the trend of how, why, when and where of spread of Covid-19 pandemic. This study done as part of Intel OneAPI hackathon is essential for tackling similar situations in the future, and making our world a safer place to live in.
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URL: https://github.com/dishitamohan/Water_Quality_Prediction_Intel_OneAPI_Hackathon/tree/main
Solving the water prediction problem using the basics of Data Analysis and several Machine Learning Algorithms and Deep Learning.
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URL: https://github.com/reeshmashahiras/water_quality_prediction
Developed an advanced water quality prediction model using the Intel OneAPI Toolkit and seamlessly integrated it with a water-focused chatbot. This synergy enables real-time monitoring, and data-driven decision-making, revolutionizing water resource management and promoting environmental awareness.
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Firstly, it is a multi-modal dataset containing different data sources such as videos, biological analysis data, and participant data. Secondly, it is the first dataset of that kind in the field of human reproduction. It consists of anonymized data from 85 different participants.
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URL: https://github.com/Ahamedthaiyub/Viginet-27
"Viginet: Your Cybersecurity Shield Defend with Machine Learning, Detect with Precision. Stay Ahead of Threats."
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URL: https://github.com/Aditya3012Purwar/Intel-oneAPI/
This project is about water quality prediction using and without using oneAPI libraries like oneDAL and oneDNN for Random Forest Classification, Logistic Regression, Support Vector Classifier, Fully Connected Neural Networks and XGBoost Classifier
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URL: https://github.com/balasuriyaranganathan/brain_tumor_classification
This Python script is designed for image classification using a pre-trained MobileNetV2 model in TensorFlow. It employs transfer learning to adapt a pre-trained model to classify images into multiple categories. The code performs the following steps: Data Preprocessing: It uses an ImageDataGenerator
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