My projects from the Stanford Machine Learning course offered on Coursera by Professor Andrew Ng.
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Updated
Sep 15, 2016 - MATLAB
My projects from the Stanford Machine Learning course offered on Coursera by Professor Andrew Ng.
A set of ML algorithms implemented in MATLAB
Exercices course of machine learning https://www.coursera.org/learn/machine-learning
Implementation of various Machine Learning (ML) Algorithms learned in the Machine Learning course authorised by Stanford University @ Coursera
EMARO 1st year final semester project in Unsupervised Machine Learning.
This project focuses on detecting and analyzing wear in drill bits during the drilling process. It involves studying three types of drill wear (flank, chisel, and outer corner wear) along with a healthy drill condition, using four corresponding datasets. The goal is to determine the most effective strategy for identifying drill bit wear.
Implement different Machine learning algorithms
Automated Spatiotemporal Thermal Anomaly Detection (ASTAD) Algorithm
Stanford's Machine Learning MOOC from Coursera
This repository contains my submissions of all the assignments for a certified course on Coursera
Implementation of Machine Learning algorithms using MatLab.
Code for the exercises of the Machine Learning course offered by Stanford University on Coursera.
Learning and codes of Andrew NG's Machine Learning course from Stanford University
Medical Image Segmentation and Anatomical Measurement Extraction with MATLAB & Python.
ML - Anomaly Detection & Recommender Systems - Python
A 12-week course I completed from Stanford Coursera to understand the mathematical and statistical rigor behind some of the most frequently-used machine learning algorithms.
Machine Learning (Stanford University) Week 9 assignments solutions
Assignments of Machine Learning Course created by Stanford University taught by Andrew Ng
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