Coursera-Machine-Learning-Andrew-NG
This is a repository of my coursera Machine Learning by Standford, Andrew NG course's assignments' solution
This is all written in matlab.The datasets are also uploaded with the excercises
Includes:
- Linear Regression (one variable and multiple variables)
- Logistic Regression
- Regularization
- Neural networks
- Support Vector Machine
- Clustering
- Dimensionality Reduction
- Anomaly Detection
- Recommender System
For more information, please visit: https://www.coursera.org/learn/machine-learning
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Here I want to recommend a course on machine learning from Andrew Ng. And as I am watching the video, I find it more efficient to watch the video together with blogs, and I think the following one is
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这段时间看了andrew .Ng老师的课程，算是机器学习的入门，感觉很不错，结合自己的对机器学习的了解，在这里将这段时间的学习总结一下 在第一讲介绍性的，讲了什么是机器学习，有监督学习（supervised learning）和无监督学习（unsupervised learning），监督学习和非监督学习，其实主要的区别在于，训练集，监督学习使用有标记的训练集，通过学习完成参数优化，
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sigmoidGradient.m function g = sigmoidGradient(z) %SIGMOIDGRADIENT returns the gradient of the sigmoid function %evaluated at z % g = SIGMOIDGRADIENT(z) computes the gradient of the sigmoid function
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lrCostFunction.m function [J, grad] = lrCostFunction(theta, X, y, lambda) %LRCOSTFUNCTION Compute cost and gradient for logistic regression with %regularization % J = LRCOSTFUNCTION(theta, X, y, la
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linearRegCostFunction.m function [J, grad] = linearRegCostFunction(X, y, theta, lambda) %LINEARREGCOSTFUNCTION Compute cost and gradient for regularized linear %regression with multiple variables %
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warmUpExercise.m function A = warmUpExercise() %WARMUPEXERCISE Example function in octave % A = WARMUPEXERCISE() is an example function that returns the 5x5 identity matrix A = []; % =============
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关于视频资源的几个问题 1.视频来自哪里？ 视频本题主从 youtube下载. 2.视频为什么不全？ 2016/9/17包括了第一周的视频。以后会再次更新。 视频下载地址 链接：http://pan.baidu.com/s/1miJbkPq 密码：6p7u
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Coursera Machine Learning Assignments in Matlab 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 i
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My Solution to Assignments of Machine-Learning on Coursera This is my solution to the assignments of Machine-Learning on Coursera.Machine-Learning on Coursera isa classical class, whose advisor is And
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Deep Learning Specialization Projects from the Deep Learning Specialization from deeplearning.ai offered by Coursera. Instructor: Andrew Ng Master Deep Learning and Break Into AI If you want to break
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学习意味着通过学习或经验获得知识或技能。 基于此，我们可以定义机器学习（ML）如下 - 它可以被定义为计算机科学领域，更具体地说是人工智能的应用，其为计算机系统提供了学习数据和从经验改进而无需明确编程的能力。 基本上，机器学习的主要焦点是允许计算机自动学习而无需人为干预。 现在问题是如何开始和完成这种学习？ 它可以从数据的观察开始。 数据可以是一些示例，指令或一些直接经验。 然后在此输入的基础上，
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Machine Learning This project provides a web-interface,as well as a programmatic-apifor various machine learning algorithms. Supported algorithms: Support Vector Machine (SVM) Support Vector Regressio
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Deep Learning Specialization on Coursera Instructor: Andrew Ng Just completed Deep Learning Specialization on Coursera, using this repo to keep a record of all my completed coursework and related file