Giter VIP home page Giter VIP logo

machine-learning-andrew-ng's Introduction

Coursera Machine Learning Assignments in Matlab

Author Matlab License contribution

title-image

Introduction


这是Coursera网站上,课程Machine Learning中算法在Matlab语言的实现,同样也可以参考斯坦福大学的计算机课程CS229

Attention:


  • 你可以在百度云上下载全套课程视频和相关文档;

Definition


  • "A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E." -------------- Definition of Machine Learning by Tom Mitchell

Enviroment


  • Windows10
  • Matlab 2017b

Target


  • 掌握机器学习的算法原理与推理过程;
  • 掌握机器学习算法在Matlab语言的实现过程和细节;

Contents

  • README.md:说明文档
  • Linear Regression
  • Linear Regression with multiple variables
  • Logistic Regression
  • Logistic Regression with Regularization
  • Multiclass Classification
  • Neural Networks Prediction fuction
  • Neural Networks Learning
  • Regularized Linear Regression
  • Bias vs. Variance
  • Support Vector Machines
  • Spam email Classifier
  • K-means Clustering
  • Principal Component Analysis
  • Anomaly Detection
  • Recommender Systems
  • Simple Gaussian Process Regression

Acknowledge

你可以检查与修改我在github上的代码仓库,欢迎任何改进和讨论。

machine-learning-andrew-ng's People

Contributors

shimengjie avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar

machine-learning-andrew-ng's Issues

图片输出问题

display_array[pad + j * (height + pad) + np.arange(height),
pad + i * (width + pad) + np.arange(width)[:, np.newaxis]] =
x[current_image, :].reshape((height, width)) / max_val
您好,我遇到一个问题,您ex3的displayData文件中的上述代码如果我换成
display_array[pad + j * (height+1):(j+1)* (height + pad),
pad + i * (width + pad) :(i+1) * (width + pad) ] =
x[current_image, :].reshape((height, width)) / max_val,输出的数字为什么发生了旋转了类似的变化。这是什么原因,您有遇到过吗?

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.