develop Vector Vector Product

GitHub Repo https://github.com/sahidesu25/Sentiment-Analysis-on-Amazon-Product-Reviews

sahidesu25/Sentiment-Analysis-on-Amazon-Product-Reviews

With the explosion of social networking sites, blogs and review sites a lot of information is available on the web. This information contains emotions and opinions about various product features and the makers of these products. This form of opinion and feedback is important to the companies developing these products as well as the companies that want to develop better rival products. Sentiment Analysis is the task of analyzing all this data, retrieving opinions about these products and services and classifying them as positive or negative, in other words good or bad. The key parts of any review of any product are the numeric rating and the textual description provided along with this product. In our project we will take into consideration both these vectors for product reviews to conclusively decide on a classifier that is best suited to analysis of product reviews. We have gathered reviews and based on the features that best describe the sentiment for each review, we have created a feature set of 1000 features, and with this limited set we will determine which classifier gives the best result on review type data. To determine the best classifier we perform evaluations on it, by running various data set generators, calculating the resubstitution and generalization errors for each classifier. We then use the mean of these results to compute the paired Student’s t-test to relatively compare the performance of the classifiers. Based on the results of this evaluation, we can state which is the best classifier.

GitHub Repo https://github.com/diegocastelo/Vectors-and-Matrices-Operations

diegocastelo/Vectors-and-Matrices-Operations

Java code where you can add, multiply, do the gaussian elimination and get the product of two matrices. Project developed with @gustavoggh, @jvleles and Daniel Chaves.

GitHub Repo https://github.com/rajat184/VectorOperations-Simulation-in-gem5

rajat184/VectorOperations-Simulation-in-gem5

Developed VectorOperations SimObject in gem5 for cross-product, normalization, and subtraction at specific ticks. Real-time dynamic event handling ensures efficient computation without storing intermediate values

GitHub Repo https://github.com/aditya-jha-kumar/Vector-Ecommerce-website

aditya-jha-kumar/Vector-Ecommerce-website

Vector is an E-commerce website with a user-friendly interface for customers to browse products, add items to their cart, and save items for later. Developed responsive front end using JavaScript, HTML, and CSS

GitHub Repo https://github.com/JihoonChung/CTC-Product-and-Store-Vectorization

JihoonChung/CTC-Product-and-Store-Vectorization

This project is a collaboration between the University of Toronto and Canadian Tire Corporation, aimed at developing advanced embedding methods for AI/ML applications to improve data representation and model performance.

GitHub Repo https://github.com/JariatunIslam/Product-Sales-Prediction-Using-Support-Vector-Machines-SVM-and-Naive-Bayes

JariatunIslam/Product-Sales-Prediction-Using-Support-Vector-Machines-SVM-and-Naive-Bayes

The primary objective is to develop a system that can predict product sales through the utilization of historical sales data.

GitHub Repo https://github.com/Ayoob7/facenet-face-recognition

Ayoob7/facenet-face-recognition

This is the research product of the thesis manifold Learning of Latent Space Vectors in GAN for Image Synthesis. This has an application to the research, name a facial recognition system. The application was developed by consulting the FaceNet model.

GitHub Repo https://github.com/gupta1vipin/springboot-productmatcher

gupta1vipin/springboot-productmatcher

This is an API developed on SpringBoot for a specific product vector matcher use-case

GitHub Repo https://github.com/ToriLiv/vector_calculator

ToriLiv/vector_calculator

Developed with HTML, CSS & JavaScript application for computing vector operations including addition, subtraction and dot products.

GitHub Repo https://github.com/pruggerd/Structural-Vector-Autoregression-Modeling

pruggerd/Structural-Vector-Autoregression-Modeling

I analyze the interplay of three U.S. time series: unemployment, inflation and gross domestic product. The first cleans the data and invests seasonality and stationarity. The second part develops a (structural) vector autoregressive model and test structural identification. The third uses principal compnent analysis and three different quality criterions to forecast quarterly U.S. GDP.