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cmontalvo251 / repository
This is my public repo of all my MATLAB Screen cast codes and other random codes written in MATLAB
MATLAB Fun Games over the years.
I have a textbook on MATLAB on my other Github repo: https://github.com/cmontalvo251/LaTeX/tree/master/Numerical_Methods_Montalvo
Also avaiable on MATLAB File EXchange
Screen Cast Codes - If you've watched one of my youtube videos and you're looking for code from one of those videos this is the folder you need to open
Tuppers - Playing with Tuppers Referential Formula
ZBiddy - Trying to hack Zbiddy but it ended up being a total scam
Sundial - A script that explains how sundials work and the equation of time
agarmyo - Based on the fun actual game called agar.io
Boids - Simulating Flocks of Birds
Conway - Conway's Game of Life
Genetic Glider - Using a genetic algorithm to converge on an aircraft that flies.
Images - Deconstruct an image using eigenvalue decomposition
NOAA_World - Plot the wind velocity as a function of days over a year around the world
PictoDots - Convert an image to dots
Planets - Simulate the birth of our solar system
Sumobots - a Fun game where you must control a bot to knock the other bot out of the screen
Traffic - Simulate traffic on a multi-lane highway
Color_Illusions - A script to illustrate color illusions
Project Euler - Go Check out projecteuler.net - Here are my solutions to some of those problems
Boat - A pretty awesome boat simulation you can run autonomously or even with keyboard inputs
Selected from shared topics, language and repository description—not editorial ratings.
PrasannaNatarajan /
This is a repository of my coursera Machine Learning by Standford, Andrew NG course's assignments
Wangxh329 /
This is my undergraduate thesis about high-performance discrete particle swarm optimization (PSO) algorithm and software development of application on JSSP problem.
radifantaufik /
This repository is a 2D travel-time tomography seismic using MATLAB which I build and my friend Rinta in order to complete my Final Projects. The forward modelling is resolved using Fast Marching Method (FMM) with finite difference approximation and the raytracing is resolved based on John Vidale paper, Finite difference calculation of travel times. This code can use two method in inversion part, Least Square and Pseudo-Inverse where the input data is only needed travel time and the location of station (in UTM, both easting and northing). You can also set some parameters which could affects the tomography result, such as the number of iteration, displaying forward modelling or inverse modelling to track your data, save your model or not and etc.
Ashleshk /
# Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. After completing this course you will get a broad idea of Machine learning algorithms. Try to solve all the assignments by yourself first, but if you get stuck somewhere then feel free to browse the code. ## Contents * Lectures Slides * Solution to programming assignment * Solution to Quizzes by Andrew Ng, Stanford University, [Coursera](https://www.coursera.org/learn/machine-learning/home/welcome) ### Week 1 - [X] Videos: Introduction - [X] Quiz: Introduction - [X] Videos: Linear Regression with One Variable - [X] Quiz: Linear Regression with One Variable ### Week 2 - [X] Videos: Linear Regression with Multiple Variables - [X] Quiz: Linear Regression with Multiple Variables - [X] Videos: Octave/Matlab Tutorial - [X] Quiz: Octave/Matlab Tutorial - [X] Programming Assignment: Linear Regression ### Week 3 - [X] Videos: Logistic Regression - [X] Quiz: Logistic Regression - [X] Videos: Regularization - [X] Quiz: Regularization - [X] Programming Assignment: Logistic Regression ### Week 4 - [X] Videos: Neural Networks: Representation - [X] Quiz: Neural Networks: Representation - [X] Programming Assignment: Multi-class Classification and Neural Networks ### Week 5 - [X] Videos: Neural Networks: Learning - [X] Quiz: Neural Networks: Learning - [X] Programming Assignment: Neural Network Learning ### Week 6 - [X] Videos: Advice for Applying Machine Learning - [X] Quiz: Advice for Applying Machine Learning - [X] Videos: Programming Assignment: Regularized Linear Regression and Bias/Variance - [X] Machine Learning System Design - [X] Quiz: Machine Learning System Design ### Week 7 - [X] Videos: Support Vector Machines - [X] Quiz: Support Vector Machines - [X] Programming Assignment: Support Vector Machines ### Week 8 - [X] Videos: Unsupervised Learning - [X] Quiz: Unsupervised Learning - [X] Videos: Dimensionality Reduction - [X] Quiz: Principal Component Analysis - [X] Programming Assignment: K-Means Clustering and PCA ### Week 9 - [X] Videos: Anomaly Detection - [X] Quiz: Anomaly Detection - [X] Videos: Recommender Systems - [X] Quiz: Recommender Systems - [X] Programming Assignment: Anomaly Detection and Recommender Systems ### Week 10 - [X] Videos: Large Scale Machine Learning - [X] Quiz: Large Scale Machine Learning ### Week 11 - [X] Videos: Application Example: Photo OCR - [X] Quiz: Application: Photo OCR ## Certificate * [Verified Certificate]() ## References [[1] Machine Learning - Stanford University](https://www.coursera.org/learn/machine-learning)
NischalSehrawat /
This is a MATLAB code to simulate an offshore wind turbine that I developed during my master thesis
arron2003 /
Matlab codes that convert a RGBD image into a cad like model. This code is released as a part of my PhD dissertation.