This project used a simple naive bayes classifier to classify different comments as five star or a one star rating. This project was a part of assignment in the subject Intro to AI.
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Updated
Jun 1, 2024 - Python
This project used a simple naive bayes classifier to classify different comments as five star or a one star rating. This project was a part of assignment in the subject Intro to AI.
Model buat TA Sentimen and Topik Berita Indonesia
This project uses the Multinomial Naive Bayes classifier to enhance movie genre classification based on metadata such as descriptions and ratings. Utilizing a dataset from Kaggle, it aims to improve content recommendation systems through accurate genre prediction.
This repository is a collection of programs implemented as part of Machine Learning Laboratory course at JSS Science And Technology University(SJCE).
Slides, exercises, and exams for my course "Natural Language Processing" (École Pour l'Informatique et les Techniques Avancées, 2024)
Python implementation of naive bayes from scratch and using scikit-learn
Enhancing Patient Care through AI-Driven Disease Prediction
Program data mining menggunakan algoritma Naive Bayes
This project examines various machine learning models for classifying text (restaurant and movie reviews) and images (CIFAR-10 dataset)
5 different kinds of machine learning alorithms has been used for the classfication of the animals and have been compared with each other
👩💻This repository contains implementations of various machine learning algorithms, along with example datasets and Jupyter Notebook files for demonstration.
This project consists of a variety of data with "spam" and "ham" emails in it. The dataset was cleaned analyzed and trained to detect the emails with the help of machine learning. Two models of Naive Bayes are compared in it,"Gaussian Naive Bayes", and "Multinomial Naive Bayes".
An 87% efficient Spam Filter implemented from scratch using Naive Bayes Algorithm.
This Repository consists of algorithms related to AI-ML. Few examples include - KNN, Naive Bayes, Decision Trees, etc.
Implemented Machine Learning Models to predict Stroke
Proyek ini bertujuan untuk melakukan klasifikasi menggunakan dua model pembelajaran mesin: Naive Bayes dan Regresi Logistik. Hasil prediksi dan akurasi dari kedua model akan dibandingkan dan divisualisasikan.
Customer Attrition Prediction with Python
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