Rosette API Client Library for Python

🚀🚀 Fetch, parse, categorize, summarize user reviews 🚀🚀

code and link to the dataset for Kenyan Food detection paper accepted as a paper in MADiMA 2019 Workshop as part of ACM MM 2019 conference.

Datasets and Code for MaskCOV (accepted in Pattern Recognition)

Domain Enrichment Toolkit $ pip install richkit

Multi-class text categorization using state-of-the-art pre-trained contextualized language models, e.g. BERT

This repository consists of a CNN based Deep Learning project. The web interface will ask user to upload an image and will predict the class of image as "Cat" or "Dog".

An Bayesian optimal experimental design framework to discriminate between active learning models in Cognitive Science

Mapping College Neighbourhood and Social Possibilities Under University Grants Commission(UGC) of India

This is a python script project that will help you categorize and organize your files according to their extensions.

This is a set of python scripts that will be used to query dbpedia through sparql for information about certain keywords.

An efficient text classification pipeline for email subjects, leveraging NLP techniques and Multinomial Naive Bayes. Easily preprocess data, train the model, and categorize new email subjects. Ideal for NLP enthusiasts and those building practical email categorization systems using Python.

Naive Bayes algorithm for multi-category text classification.

This tool provides an easy way to generate a preferences profile of a given Twitter user.

Helper tools for the qimgv image viewer

App para detetar e separar maçãs em pequenas, grandes ou defeituosas. / App to detect and sort apples in small, big or defective.

In this repository, we deal with the FashionMNIST classification using deep multilayer perceptron (MLP) models as well as using deep convolutional neural networks (CNN) models.

Software to automate the categorization and classification of code-snippets.

This project determines the sentiment of each tweet and the cluster classifies the same into four categories.