The aim of this repo is to contribute to the diagnosis of epilepsy by taking advantage of the engineering. So, for diagnosing of epileptic seizures from EEG signals are transformed discrete wavelet and auto regressive models. After these transformations, extract data is applied input for Back-propagation, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM) ,ANN ,Logistic Regression and Principal Component Analysis algorithms.

An NLP research project utilizing the "cardiffnlp/twitter-roberta-base-sentiment-latest" pre-trained transformer for tweet tokenization. The project includes an attention-based biLSTM model that predicts sentiment labels for tweets as negative (-1), neutral (0), or positive (1).

Non-contextual : Word2Vec, FastText Contextual : BERT, RoBERTa, ELECTRA, CamemBERT, Distil-BERT, XLM-RoBERTa Analyzed embedding models, used the best one to build a Flask web app for Hindi NER and data collection from user feedback, deployed on AWS.

This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.

Advanced topics in ML

No description provided.

A comparative analysis of various machine learning models for time series forecasting, including traditional methods and LLMs.

No description provided.

This repository includes problem set questions for the Machine Learning course held in Spring 2025 at CS dept. of Shahid Beheshti University.

Collection of some classical Machine learning Algorithms.

This repo is a set of curated resources covering traditional machine learning algorithms and techniques.

These training sessions in machine learning, conducted by Yandex, are dedicated to classical machine learning. This offers an opportunity to reinforce theoretical knowledge through practice on training tasks.

Detecting deepfakes using both CNN and classical Machine Learning

Project to learn linear regression using python, statsmodels and scikit-learn

Classical Machine Learning Concepts + Basic WebScraping + Numpy and Pandas libraries

[SHL 2021] Official Implementation of the Paper "Classical Machine Learning Approach for Human Activity Recognition Using Location Data"

It will be shown how to train a quantum machine learning model to overcome a classification problem.

Analyzing and comparing the performance of various machine learning models on multiple datasets. The models implemented include Logistic Regression, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Neural Networks (both fully connected and convolutional).

pylearn_ml191: An implementation of some classical machine learning algorithm

No description provided.

This repository includes problem set questions for the Data Science course held in Spring 2025 at CS dept. of Shahid Beheshti University.

Contains experiments in classical machine learning, for personal reference

Comprehensive evaluation and optimization of classical machine learning models for sentiment analysis of movie reviews, leveraging optimized data analysis, preprocessing, and feature engineering

end to end machine learning projects

Simple and flexible classical ML module that can be used for recording baseline ML performance.

A open source playground for classical Machine Learning Stuffs

This project detects abusive and non-abusive comments in Malayalm Language using the MuRIL Bert model and compares its performance with TF-IDF + SVM and XGBoost. MuRIL outperforms classical models.

Classification of handwritten digits using classical machine learning methods with model optimization and evaluation on the Scikit-learn Digits dataset

No description provided.

A smart question tagging and matching system using traditional ML and NLP. It finds similar questions, tags them, and groups related ones to reduce duplicates. Built with TF-IDF, cosine similarity , KMeans & XgBoost, GBDT,Logistic Regression for fast, scalable, and real-world use.