A class for performing principal component analysis using Eigen3 library
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Updated
Nov 10, 2020 - C++
A class for performing principal component analysis using Eigen3 library
Worked on building a predictive model by considering multi collinearity and applying regression technique as well as other machine learning concepts related to factors or variables using SAS programming.
Matlab files for data analytics methods
Evaluating the performance of classifiers in a fraud detection application
CDAC UChicago SEM Image Classification, Fuel Spill Classification, and Publishing to DLHub
Face Recognition Using PCA and LDA
The thing of beauty in baseball is that each year we have a chance to see players making a leap. Like Jose Bautista, Jose Ramirez, Ben Zobrist, etc. This research aims to find out of these breakout players, the improvement of what stats are more responsible for their WAR and wRC+ gain.
Business Problem Overview In the telecom industry, customers are able to choose from multiple service providers and actively switch from one operator to another. In this highly competitive market, the telecommunications industry experiences an average of 15-25% annual churn rate. Given the fact that it costs 5-10 times more to acquire a new cust…
The quality of the famous red wine dataset is predicted using Linear regression. The quality of the wine is also classified using logistic regression, SVM, Naive Bayesian, linear regressor as classifier. PCA analysis is also applied on the same
Basic ML algorithm implementation in python
An analysis of human genome mutations from different populations.
Problem Sets and Final Exam for Texas A&M ECMT 670: Machine Learning in Econometrics
Machine learning model which can predict the strength of a mixture for given composition of ingredients like cement, slag, ash, water, superplastic, coarse aggregates, fine aggregates, age.
Neural Networks, Dimensionality Reduction and Clustering
Hiphop or Rock? My goal is to classify songs as being either 'Hip-Hop' or 'Rock' - all without listening to a single one ourselves
Use unsupervised learning by fitting data to a model and using clustering algorithms to place data into groups of patients with or without myopia. Then, create a visualization that shares your findings.
This repository contains the code and conclusions from a Breast Cancer Detection Machine Learning project. This project using FNA imaging and classification models to determine if breast cancer cells are malignant or benign
🧠 DMAD - Differential Morphing Attack Detection. A project for Fundamentals of Computer Vision and Biometrics course at the University of Salerno.
This project creates predictions about Cryptocurrency using Unsupervised Machine Learning model.
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