process Vector Product Vector

GitHub Repo https://github.com/UtkarshPanara/Predicting-product-quality-for-Tennesee-Eastman-process

UtkarshPanara/Predicting-product-quality-for-Tennesee-Eastman-process

Prediction of product quality using Deep Neural Network and Support Vector Regression

GitHub Repo https://github.com/AndreasBraun5/Data-Mining-in-Industrial-Processes-Evaluation-of-different-machine-learning-models-for-Prediction

AndreasBraun5/Data-Mining-in-Industrial-Processes-Evaluation-of-different-machine-learning-models-for-Prediction

Data Mining in Industrial Processes: Evaluation of different machine learning models for product quality prediction. Evaluated model types are Random Forest, Naive Gaussian Bayes, Logistic Regression, K Nearest Neighbour and Support Vector Machine. Comparision of non time based state based approach with time series based approach. Final result in precision 99.83 %.

GitHub Repo https://github.com/Alamart1683/mpi-vectors-scalar-product-for-n-process

Alamart1683/mpi-vectors-scalar-product-for-n-process

Вычисление скалярного произведения векторов с помощью MPI

GitHub Repo https://github.com/Amagnum/Parallel-Dot-Product-of-2-vectors-MPI

Amagnum/Parallel-Dot-Product-of-2-vectors-MPI

Computing the vector-vector multiplication on p processors using block-striped partitioning for uniform data distribution. Assuming that the vectors are of size n and p is the number of processors used and n is a multiple of p.

GitHub Repo https://github.com/priyanka387/LangChain-Vector-Databases-in-Production

priyanka387/LangChain-Vector-Databases-in-Production

LLMs are deep learning models with billions of parameters that excel at a wide range of natural language processing tasks. They can perform tasks like translation, sentiment analysis, and chatbot conversations without being specifically trained for them

GitHub Repo https://github.com/zer0-A1/Semantic_Search

zer0-A1/Semantic_Search

A FastAPI semantic search system for company/product data. It processes Excel/CSV files, uses OpenAI's text-embedding-3-small model to generate AI embeddings, and performs vector similarity searches via PostgreSQL with pgvector.

GitHub Repo https://github.com/DheerajKumar97/Amazon-Product-Reviews-LSTM--NLP-with-Deployment

DheerajKumar97/Amazon-Product-Reviews-LSTM--NLP-with-Deployment

This project is designed to predict Amazon Product review sentiment analysis and this analysis is used to give feedback about the quality of the Products. This project is implemented using Natural Language processing using a bag of words model and other techniques like vectorization to analyze the product reviews.

GitHub Repo https://github.com/shruti821/Leaf-Disease-Detection-Using-Image-Processing

shruti821/Leaf-Disease-Detection-Using-Image-Processing

Agricultural productivity is something on which economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. For instance a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. This paper introduces an efficient approach to identify healthy and diseased or an infected leaf using image processing and machine learning techniques. Various diseases damage the chlorophyll of leaves and affect with brown or black marks on the leaf area. These can be detected using image prepossessing, image segmentation. Support Vector Machine (SVM) is one of the machine learning algorithms is used for classification. The Convolutional Neural Network (CNN) resulted in a improved accuracy of recognition compared to the SVM approach.

GitHub Repo https://github.com/Mizanur888/VectorDotProductWith_MPI_Scatter

Mizanur888/VectorDotProductWith_MPI_Scatter

In this assignment we parallelize the matrix-vector product to calculate dot product more efficiently. To reducing the calculation time, we send chunks to array to different processes, so that each process can calculate the dot product of chunks of array. Also, we calculate the start, end and total time to determine how long it taken by each process.

GitHub Repo https://github.com/binoydutt/Resume-Job-Description-Matching

binoydutt/Resume-Job-Description-Matching

The purpose of this project was to defeat the current Application Tracking System used by most of the organization to filter out resumes. In order to achieve this goal I had to come up with a universal score which can help the applicant understand the current status of the match. The following steps were undertaken for this project 1) Job Descriptions were collected from Glass Door Web Site using Selenium as other scrappers failed 2) PDF resume parsing using PDF Miner 3) Creating a vector representation of each Job Description - Used word2Vec to create the vector in 300-dimensional vector space with each document represented as a list of word vectors 4) Given each word its required weights to counter few Job Description specific words to be dealt with - Used TFIDF score to get the word weights. 5) Important skill related words were given higher weights and overall mean of each Job description was obtained using the product for word vector and its TFIDF scores 6) Cosine Similarity was used get the similarities of the Job Description and the Resume 7) Various Natural Language Processing Techniques were identified to suggest on the improvements in the resume that could help increase the match score