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Star 152. master. README. MIT license. Machine Learning By Prof. Andrew Ng 🌟🌟🌟🌟⭐. This page contains all my YouTube/Coursera Machine Learning courses and resources 📖 by Prof. Andrew Ng 👨. Table of Contents. Brief Intro. Video lectures Index. Programming Exercise Tutorials. Programming Exercise Test Cases. Useful Resources. Schedule.
1;:::;ng|is called a training set. Note that the superscript \(i)" in the notation is simply an index into the training set, and has nothing to do with exponentiation. We will also use Xdenote the space of input values, and Y the space of output values. In this example, X= Y= R. To describe the supervised learning problem slightly more formally ...
Machine-Learning-Notes. Collection of my hand-written notes, lectures pdfs, and tips for applying ML in problem solving. Resource are mostly from online course platforms like DataCamp, Coursera and Udacity.
Stanford Machine Learning. The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester.
This repository contains a collection of notes and implementations of machine learning algorithms from Andrew Ng's machine learning specialization. The specialization consists of three courses: Supervised Machine Learning: Regression and Classification. Advanced Learning Algorithms.
Stanford Machine Learning. The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester.
To describe the supervised learning problem slightly more formally, our goal is, given a training set, to learn a function h : X → Y so that h(x) is a “good” predictor for the corresponding value of y.
