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An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.
Final Year project based upon Network Intrusion Detection System
Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting
Recognition of Persomnality Types from Facebook status using Machine Learning
A model that could accurately predict the Industry Domain for different start-ups and companies based on descriptions, titles and categories.
This project presents Hera, an Operating System level voice recognition package that understands voice commands to perform actions to simplify the user’s workflow. We propose a modernistic way of interacting with Linux systems, where the latency of conventional physical inputs are minimized through the use of natural language speech recognition.
Classifying Forest Cover type
Classifying a website based on it's URL. I've implemented Stochastic Gradient Descent, Multinomial Naive Bayes and Convolutional Neural Network for classifying the category of the URL.
The objective of this project is to classify whether upcoming product will have positive or negative Sentiment.
Auto Classify Text
Recognize Handwritten Digits(persian/english) with Neural Networks
Sharing both theoretical and programing ideas, that I came across at Introduction to Machine Learning course. notes, homework solution and python assignment
Multiclass classification of Youtube videos using text mining.
Paid Promoters Recommender project objective is to make a recommendation system that recommends youtube content creators relevant to ads of advertisers.
A machine learning model that predicts tags for a given question and body.
In this notebook I've build a nlp/machine learning model that classify hotel-reviews.
An Automated tag prediction system for the question posted on stack overflow is done using machine learning
Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.
An automated tag prediction system on stackoverflow
A simple UN sustainable development goals classifier using SGD classifier for modeling and streamlit for UI
This project implements an NLP-based solution for filtering out e-mails as ham or spam.
In this challenge, I build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).
Le Machine Learning, aussi appelé apprentissage automatique en français, est une forme d’intelligence artificielle permettant aux ordinateurs d’apprendre sans avoir été programmés explicitement à cet effet.
Perceptron, Pseudo Inverse Linear Classifier, SGD, SVM, Batch Gradient Descent, Minibatch Gradient Descent with tensorflow
NLP Classification and Clustering with spam SMS dataset
Using Spark Streaming and Spark MLlib (via PySpark) to perform Sentiment Analysis on a dataset of Tweets.
MNIST Handwritten Digits Classification
Trabajo Práctico Final para la materia Organización de Datos 75.06 - UBA. Score máximo obtenido de 0.83726 para la competencia 'Real or Not? NLP with Disaster Tweets' de Kaggle.
This repository has been established in order to train fundamental concepts in machine learning with some examples.
A submission for HUAWEI - 2020 DIGIX GLOBAL AI CHALLENGE
Classified the types of URL using machine learning algorithms.
This is a very simple model to predict Iris flower species. we have three types of species in it (Versicolor, Verginica, Setosa).
The Mid-term 'Natural Language Processing' project by Duc Tran Van, Minh Nguyen Tan, Trung Nguyen Hoang
Solved Classification Problems
This project detects AI-generated text using an ensemble of classifiers: Multinomial Naive Bayes, Logistic Regression, LightGBM, and CatBoost. It includes robust data preprocessing, model development, and evaluation, ensuring accurate identification of AI-generated content from a diverse text dataset.