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.
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Updated
Nov 2, 2021 - HTML
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.
A ggplot2 based biplot for principal components-like methods
📙 End-to-end NLP and data visualization pipeline of the text from a machine learning textbook.
Principal Component Analysis is One of the Most Popular Dimensionality Reduction Algorithms used in Machine Learning Which comes under Unsupervised Way of Learning. It is also Used as a way of Feature Extraction where, More Information is Extracted from all the Existing Attributes, in just some 3-4 Attributes using the Concepts of Eigen Values a…
Slides, exercises, and exams for my course "Statistical Learning with R" (Ecole Normale Supérieure Paris-Saclay, 2023)
code for Visualizing and Understanding the Relationship between PCA, Auto encoder and K-Means Clustering.
Principal components analysis on decathlon data in R.
Objective of this project is to identify the in-control data points and eliminate out of control data points to set up distribution parameters for manufacturing process monitoring. I utilized PCA for dimension reduction and Hotelling T2 and m-CUSUM control charts to established mean and variance matrices.
Introduction to Machine Learning & Deep Learning
This repository contains code for my Machine Learning Basic Nanodegree Project.
A topic designed by Warwick Business School requires students to enhance loan portfolio management by utilising cluster analysis to group borrowers with similar characteristics, enabling personalised loan products, targeted marketing strategies, and a better customer support process to serve the unique needs of each segment through cluster analysis
My personal repository for all of my work for the Battling the Curse of Dimensionality course at UU in the fall of 2021.
Projects that I have done on Data Science
Apply unsupervised learning techniques to identify customers segments.
Project on real-time proprietary data for Bertelsmann Arvato Analytics to identify customer segments that form the core customer base of the company using unsupervised learning techniques. Data cleaning was an integral part of the project since the data used here was real-world. Techniques like Principal Component Analysis were also used for Dim…
Multi-class Classification of physiological features into 4 classes.
Master thesis research project prepared for the MSc in Management at Barcelona School of Management.
Dimension Reduction in R
Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments
An HTML handout on principal component analysis
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