SongifyVox is an innovative voice conversion app powered by PyTorch, Intel@ One API a cutting-edge deep learning framework. This revolutionary application allows users to transform their recorded voices by choosing their favorite AI artist into captivating songs with the help of AI algorithms.
The "Live Object Detection with YOLO and OpenCV" project is a real-time object detection system that utilizes the YOLO (You Only Look Once) model and the OpenCV library to perform live object detection on a camera feed. This project aims to showcase the potential of real-time object detection and in
Image segmentation of luxury cars, worked on the Intel OpenVINO notebook with Python, Matplotlib, training the model, uploading the photo, masking the photo, to change the image color.
This project presents an enhanced approach for phishing site detection, leveraging advanced machine learning techniques. Various ML algorithms like Decision Tree, Random Forest, Multilayer Perceptrons, XGBoost, Autoencoder Neural Networks and Support Vector Machines have been compared.
Assignments and workshops, students become
aware of the breadth of Intel AI portfolio and
practical experience of the benefits of using Intel
AI software and hardware co-optimized solutions.
By default, students consider Intel's AI portfolio
for their future academic and professional AI
projects.
Recent research suggests an emerging trend in the use of artificial intelligence to exceed human capabilities. One such application of AI is Sentiment Analysis, which shows potential in assessing the performance of products, marketing campaigns, and customer services.
OORB introduces an open-source framework for building and teaching organic robotics, simplifying the journey from idea to prototype for all skill levels. Aimed at revolutionizing educational resources in advanced robotics, OORB supports coding in any language and offers an easy-to-navigate, modular
OLAWUYI RACETT NIGERIA LTD., RC14668218, has an innovative drone known as the ENVIRONMENTAL DRONE, that detects and measures the concentrations of GreenHouse Gases (GHG) (SO2, NO2, P.M.2.5, P.M10, O3, CO2, CO, NH3, and CH4) ,and also performs air abatement of these pollutants above ground level.
The Ground Robotic Oil Spill Surveillance (GROSS) System is a programmed, autonomous mobile robot that patrols beside land crude oil pipelines, and other pipelines containing petroleum products to detect the onset of spills from the pipeline within FOUR (4) MINUTES. RC14668218.
My code predicts the sentiments underlying tweets received in real time using tweepy and categorise them as positive, negative, or neutral, this script first performs EDA before preprocessing numerous datasets to train a bidirectional LSTM model.
The healthcare condition among the poor is pathetic. These people lack in quality healthcare due to increased cost, lack of doctors and medicines. Healthcare camps are the only hope for the poor people who cannot afford to pay for expensive treatments or medicines.
Therefore patients should
This project aims to build a predictive model for sentiment analysis using social media data related to a particular brand or product. The model uses LDA for topic modeling and feature extraction, and SVR for sentiment score prediction.
Welcome to TransData Rapid growth in the service and technology sectors and the heightened competition in the market have resulted in the need for businesses to increase productivity, integrate all available information, and improve the standard of customization.
Marketers and businesses can use consumer sentiment to inform their marketing strategies and improve their sales. By understanding consumer sentiment, they can tailor their messaging and advertising to appeal to their target audience. Participants will be tasked with building a predictive model that
Exploring the Fascinating World of Music Generation with LSTM Neural Networks and the MusicNet Dataset using OneDNN. Discover the process of training LSTM models, generating unique compositions, and harnessing the power of Intel DevCloud for efficient execution.
This project aims to classify air quality using a dataset on pollution levels. Employing the Random Forest model and oneAPI optimization, it achieves 99.8% accuracy. The system can aid urban planning, environmental monitoring, and public health initiatives, identifying regions with poor air quality
The combination of Stable Diffusion AI and Intel oneAPI provides a powerful solution for enhancing image quality in various applications, including photography, video processing, medical imaging, and more. It enables developers to create visually appealing and high-quality images by leveraging Intel