My projects from the Stanford Machine Learning course offered on Coursera by Professor Andrew Ng.
-
Updated
Sep 15, 2016 - MATLAB
My projects from the Stanford Machine Learning course offered on Coursera by Professor Andrew Ng.
Code for the exercises of the Machine Learning course offered by Stanford University on Coursera.
Machine Learning Algorithms for the programming tasks of Stanford online course from Andrew Ng on Coursera
Implementation of Supervised and Unsupervised algorithms
Several ML Algorithms implemented from scratch, without using inbuilt libraries. Regression Models, GDA, SVM, Naive Bayes, Decision Tree, PCA using SVD, Neural Network
Machine Learning principles in Octave/Matlab from Andrew Ng Specialization
K-Means (Lloyd's Methos) using MATLAB
Clustering and Dimensionality Reduction using k-mean and PCA.
machine-learning octave neural-networks linear-regression logistic-regression multi-class-classification support-vector-machines k-means-clustering principal-component-analysis anomaly-detection recommender-systems
Image compression using the K-means clustering algorithm | Dimensionality reduction using PCA
Course Lab work for Image analysis and computer vision
A matlab implementation for the unsupervised learning algorithm ( K-Means).
Exercises I solved for the Machine Learning course at Coursera by Andrew Ng.
Learning Maching learning through Octave and Matlab
Andrew Ng's Machine Learning Course
A jigsaw puzzle solver term project.
Recommendation system for the jester (joke) dataset using collaborative filtering and K-means clustering algorithms.
A simple program which performs K-Means clustering on a data set as well as visualizes the results.
Studying Machine Learning
Add a description, image, and links to the k-means-clustering topic page so that developers can more easily learn about it.
To associate your repository with the k-means-clustering topic, visit your repo's landing page and select "manage topics."