udacity machine learning course

and data science, and of course Scala, considering its relationship with Spark, and Julia, some developers think this is the next big thing in the programming world ". Run this query to obtain the following data: Then, I used the keyword "Machine Learning" to search again and got similar data, as shown below: So what do we get from the data? First of all, w

Professor Zhang Zhihua: machine learning--a love of statistics and computationEditorial press: This article is from Zhang Zhihua teacher in the ninth China R Language Conference and Shanghai Jiaotong University's two lectures in the sorting out. Zhang Zhihua is a professor of computer science and engineering at Shanghai Jiaotong University, adjunct professor of data Science Research Center of Shanghai Jiaot

first, gradient descent method In the machine learning algorithm, for many supervised learning models, the loss function of the original model needs to be constructed, then the loss function is optimized by the optimization algorithm in order to find the optimal parameter. In the optimization algorithm of machine

Machine learning Algorithm and Python Practice (c) Advanced support vector Machine (SVM)Machine learning Algorithm and Python Practice (c) Advanced support vector Machine (SVM)[Email protected]Http://blog.csdn.net/zouxy09Machine

Android Virtual Machine Learning summary Dalvik Virtual Machine Introduction 1. The most significant difference between a Dalvik virtual machine and a Java virtual machine is that they have different file formats and instruction sets. The Dalvik virtual

AI Bacteria Perceptron is one of the oldest classification methods, and today it seems that its classification model is not strong in generalization at most, but its principle is worth studying. Because the study of the Perceptron model, can be developed into support vector machine (by simply modifying the loss function), and can develop into a neural network (by simply stacking), so it also has a certain position. So here's a brief introduction to

) Discriminant analysis is mainly in the statistics over there, so I am not very familiar with the temporary find statistics Department of the Boudoir Honey made up a missed lesson. Here we are now learning to sell. A typical example of discriminant analysis is linear discriminant analysis (Linear discriminant analyses), referred to as LDA. (notice here not to be confused with the implied Dirichlet distribution (latent Dirichlet allocation), although

there is no prior knowledge, the Gaussian kernel is generally chosen. Why choose a Gaussian nucleus? Because you can map data to an infinite-dimensional space.Minimum optimization of the SMO sequenceThis learning method is to simply solve the parameters of the SVM algorithm, is not very important (change-^-^), so there is no very detailed look, later have time to read and then update to this article.Pending Update:Reference books:The method of statis

ObjectiveFor deep learning, novice I recommend to see UFLDL first, do not do assignment words, one or two nights can be read. After all, convolution, pooling what is not a particularly mysterious thing. The course is concise, sharply, and points out the most basic and important points.cs231n This is a complete course, the content is a bit more, although the

Gradient descent algorithm minimization of cost function J gradient descent Using the whole machine learning minimization first look at the General J () function problem We have J (θ0,θ1) we want to get min J (θ0,θ1) gradient drop for more general functions J (Θ0,θ1,θ2 .....) θn) min J (θ0,θ1,θ2 .....) Θn) How this algorithm works. : Starting from the initial assumption Starting from 0, 0 (or any other valu

The topic of machine learning techniques under this column (machine learning) is a personal learning experience and notes on the Machine Learning Techniques (2015) of Coursera public

Course Description: This is an introductory course on deep learning, and deep learning is mainly used for machine translation, image recognition, games, image generation and more. The course also has two very interesting practical