Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Weighted Class TFIDF technique to deal with imbalanced datasets

Conversational AI designed specifically for the Marathi language using Rasa.

Scikit-learn tutorial for beginniers. How to perform classification, regression. How to measure machine learning model performacne acuuracy, presiccion, recall, ROC.

Authorship Attribution with Machine Learning

Recommendation system built using multiple ML models that aim to predict users' interests based on their past behavior and preferences.

Given a document, identifying the closest documents within the list of documents using tf-idf matrix and cosine similarity

Performed text preprocessing, clustering and analyzed the data from different books using K-means, EM, Hierarchical clustering algorithms and calculated Kappa, Consistency, Cohesion or Silhouette for the same.

All NLP related courses on DataCamp

Train model using your own dataset and use it to predict the label for a given text. Additionally, it identify if the text is likely to be spam or irrelevant.

This is final project of Information Retrieval course which is implementation of a search engine

A python package for creating content-based text recommender systems on pandas dataframes and SQLAlchemy tables

The project utilizes the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm. The main objective of this project is to measure the similarity between text documents using the TF-IDF algorithm.

Repositorio com códigos relacionados a pesquisa de TCC sobre desempenho dos algoritmos Naive Bayes, RL e SVM para classificação de revisões.

In the above 3 tasks we will study and investigate the proximity between 3 different groups of texts taken from different press sections. With reference to text mining, data cleaning, vector representation of rituals using various methods and performing various NLP tasks.

Physician clinical notes categorized into medical specialities using ML model

MailGuard is an intelligent spam detection tool that classifies emails as spam or ham using a Multinomial Naive Bayes model. Built with Streamlit, it leverages natural language processing techniques for text cleaning and feature extraction.

This project aims to develop a machine learning algorithm that can accurately detect and filter out spam comments on YouTube videos.

Repository aimed at building a simple recommender system for a content based dataset. The textual information is analysed so as to utilised as a more concrete piece of information!

Movie Counsel helps you to get tailored Movie/Series recommendation with an inbuilt Sentiment Analyzer Tool for Movie Reviews