Principal Component Analysis method of dimension reduction for feature vectors of higher space to a lower feature space

Assignments Solution for Foundations of Machine Learning Course

Principal Component Analysis and Cluster Analysis for lending club loan dataset of 27000 observations using K-means

Details of certified courses covered by me. Includes notes and solutions to programming exercises.

Customer Segmentation Analysis Based on Products Purchased Using the K-Means Method

Implementation of Persistent Homology Transform

Identifying Customer Segments using unsupervised learning techniques

This is a property tax fraud detection project using two models - PCA vs an autoencoder - to build fraud scores. The scores generated are then combined to build a single fraud score for each record.

PCA using Python

Clustering Crypto. A project that explores the following areas: Pandas DataFrames, Data Cleaning, Scaling Data, K Means, Principal Component Analysis, hvPlot, and 3-D Plotting

Simple application to visualize the result of the PCA

Predicting that the patient is suffering from Heart Disease or Myocardial Infarction (MI) based on various parameters.

Contains nongraded challenge during FTDS Batch 001-Phase 1 at Hacktiv8

⚡ Using Python NumPy and C/C++ in the Unix/Linux environment to implement a PCA voice classifier and deployed it onto a robot car.

Example of using Machine Learning (k-clustering) to determine if a dataset can be clustered.

Using several clustering algorithm to segment an insurance company customers

In this project, we use differents methods to transform our dataset (usually dimension modification) before making prediction thanks to machine learning and regressions.

Create targeted ad marketing campaign by dividing their customers into at least 3 distinctive groups.

PCA in a set of images of the Spain chamber of representatives.