coursera machine learning review

This semester has been to follow up on the Coursera Machina learning public class, the teacher Andrew Ng is one of the founders of Coursera, machine learning aspects of Daniel. This course is a choice for those who want to understand and master

Deep Learning SpecializationWunda recently launched a series of courses on deep learning in Coursera with Deeplearning.ai, which is more practical compared to the previous machine learning course. The operating language also has MATLAB changed to Python to be more fit to the

In machine learning, often need to calculate the distance between each sample, used for classification, according to distance, different samples grouped into a class; But in the current machine learning algorithm, the distance calculation mode is endless, then this blog is mainly to comb the current

Public Course address:Https://class.coursera.org/ml-003/class/index INSTRUCTOR:Andrew Ng 1. deciding what to try next ( Determine what to do next ) I have already introduced some machine learning methods. It is obviously not enough to know the specific process of these methods. The key is to learn how to use them. The so-called best way to master knowledge is to put it into practice. Consider the ear

0. OriginalDeep learning algorithms with applications to Video Analytics for A Smart city:a Survey1. Target DetectionThe goal of target detection is to pinpoint the location of the target in the image. Many work with deep learning algorithms has been proposed. We review the following representative work:SZEGEDY[28] modified the deep convolutional network, replaci

linear kernel)The neural network works well in all kinds of n, m cases, and the defect is that the training speed is slow.Reference documents[1] Andrew Ng Coursera public class seventh week[2] Kernel Functions for machine learning applications. http://crsouza.com/2010/03/kernel-functions-for-machine-

NIPS 2016 | Best Paper, Dual Learning, Review Network, VQA and other papers selectedOriginal 2016-12-12 Small S program Yuan Daily program of the Daily The most watched academic event of the past week has been the NIPS 2016 meeting in the beautiful Barcelona. Every year NIPS meetings, there will be very heavyweight tutorial and work published. Today we recommend and share the following articles: Value Iter

have been standing behind the scenes, and some things all the ins and outs only I know, because I and Dr. Huanghai, NetEase Cloud class, Professor Wunda and Coursera GTC translation platform, Deeplearning.ai official have had exchanges, so I still have to leave something as a description, Save everyone in the network every day noisy ah did not calm down to study seriously. As mentioned in this article, I have a chat record to support, some of the auth

a machine learning course at Stanford University. Take more course notes, complete course assignments as much as possible, and ask more questions. Read some books: This refers not to textbooks, but to the books listed above for beginners of programmers. Master a tool: Learn to use an analysis tool or class library, such as the python Machine

Learning, cs229tStatistical learning theory, cs231nconvolutional neural Networks for Visual recognition,cs231acomputer Vision:from 3D recontruct to recognition,cs231bThe cutting Edge of computer Vision,cs221Artificial Intelligence:principles Techniques,cs131computer vision:foundations and Applications,cs369lA Theoretical perspective on machine

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