Tools created for machine learning classification model evaluation

Automated polysomnography for experimental animal research

Face Recognition Using several dimensionality reduction techniques along with KNN as a classification algorithm

This Human Activity Recogisition analyses human activity patterns using smartphone sensor data from the UCI Human Activity Recognition dataset. It involves outlier detection, correlation analysis, and structural graph analysis. DBSCAN clustering is applied, followed by LDA for dimensionality reduction, to visualise and interpret activity clusters

"This repository contains implementations of Linear Discriminant Analysis (LDA) algorithms for data mining tasks. Linear Discriminant Analysis is a dimensionality reduction technique used to find a linear combination of features that characterizes or separates classes of data."

Machine learning library for classification tasks

Develop a Lead Prediction System to enhance marketing efforts by accurately identifying prospective customers.

This project provides a comprehensive framework for evaluating classification models and selecting the best algorithm based on performance metrics. It demonstrates the importance of hyperparameter tuning and model comparison in machine learning workflows.

Analysis of student performances of the Open University Learning Analytics dataset by using logistic regression and various classifiers.

LDA, QDA and NB in Python from scratch

Counter-Strike: Global Offensive round winner predictor based on models trained with snapshots of data across different rounds.

Machine Learning Library for Classification Tasks

Machine learning library for classification tasks

Machine learning library for classification tasks

Machine learning library for classification tasks

Machine learning library for classification tasks

Face Recognition Project using PCA and LDA Algorithms for Dimensionality Reduction

Intermediate Machine learning course with example projects

The folliwing ML project involves EDA analysis of Election Dataset, Data preparation for modelling, and prediction using ML models. Also Text Analysis on the inaugral corpora from nltk to analyse the most frequently used words in Presidents' Speeches.

Using Linear Regression, Logistic Regression and Linear Discriminant Analysis Models to make accurate predictions for different datasets.