Deliver uncompromised performance for diverse workloads across multiple architectures.
, we can evaluate the quality of water based on a range of crucial parameters, allowing us to make informed decisions about its fitness for human consumption. The suggested solution offers comprehensive exploration of various machine learning models and techniques applied to this dataset. From
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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/vidushiOmar/Intel_prj/tree/main
This project focuses on using different classification models from scikit-learn and combining them to achieve a practical model to predict the quality of water to predict if the water is drinkable or not.
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URL: https://github.com/MohitGupta0123/GARIB_General_Application_for_Rural_Income_Building
G.A.R.I.B. app aims to empower economically weak and uneducated individuals by removing barriers to loans and suitable employment, promoting equal opportunities and inclusive growth.
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URL: https://github.com/ajaypaliwal01/Intel-one-API
Agrify: a tool for precision agriculture. It is a one stop solution for farmers introducing them to the concept of precise farming. the concept of precise farming. Precision agriculture (PA) is the science of improving crop yields and assisting management decisions using sensors and data analysis.
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URL: https://github.com/rahulkumarroy477/water-potability.git
Water potability is a critical concern for ensuring safe drinking water for communities around the world. Leveraging the power of machine learning, we'll demonstrate how to build a robust model that can predict the potability of water sources with high accuracy.
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Reducing the carbon footprint by increasing the use of solar panels and decreasing the use of Coal for producing electricity, ultimately reducing carbon footprint and saving the earth from some catastrophic event/ uncertainty.
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Reducing the carbon footprint by increasing the use of solar panels and decreasing the use of Coal for producing electricity, ultimately reducing carbon footprint and saving the earth from some catastrophic event/ uncertainty.
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URL: https://github.com/iurk1702/intelOneAPI_submission
Refugee status determiner using OneAPi toolkit
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URL: https://github.com/sayashraaj/oneapi
Obtain a differentially private dataset mirroring the original while safeguarding individual privacy
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URL: https://github.com/AKHILVANKAYALA99/oneAPI-Online-AI-Hackathon/blob/main/oneAPI_Hackathon.ipynb
The project aims to predict water quality, with a focus on its suitability for consumption. Access to safe water is crucial for human survival and ecosystem preservation. The solution utilizes techniques like SMOTE and uses Random Forest Machine Learning algorithm.
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URL: https://github.com/scholar-2001/Semi_labelling/tree/master
Creating an open source auto labelling tool that labels image using pretrained models. We can then edit those labelling too using this tool. Currently, only supported for yolov5 models but working on expanding it. Also, it is using stable PyTorch in backend for better acceleration by intel libraries
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URL: https://github.com/VinayVaishnav/Water_Quality_Prediction
Using Intel's AI Analytics Toolkit we tried to predict freshwater quality, achieving an F1 score of 0.81786 with TabNet ensemble model, addressing data challenges and optimizing performance for sustainable water assessment.
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URL: https://github.com/Senthil-Riddhish/Intel-One-Api-Hackathon
Harnessed the power of Intel technologies to enhance the capabilities of the YOLOv5 algorithm for object detection. By leveraging Intel's optimized libraries and frameworks, such as Intel oneDAL, Intel optimized PyTorch, and the SYCL/DPC++ libraries, we have achieved superior performance, accuracy,
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URL: https://github.com/Ashutoshjha0007/intelunnati_AshutoshJha/tree/main
The Fashion-MNIST dataset is used as a standard for assessing how well image classification models perform. Classifying fashion items presents a difficult task that is applicable to real-world applications. I have tried to add to the body of knowledge in the field of computer vision by creating
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URL: https://github.com/shruthi2608/CureQuest/
AI revolutionizes health: Predict. Prevent. Prevail
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URL: https://github.com/SSKlearns/IntelOneAPI/
Trained ResNet-50 for 5 epochs, optimized with IPEX for 15 epochs. Converted to ONNX, further refined with OpenVINO, all on Intel Dev Cloud. The Gradio app takes video input and detects accidents.
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