netcom learning

http://blog.csdn.net/pipisorry/article/details/44904649Machine learning machines Learning-andrew NG Courses Study notesLarge Scale machines Learning large machine learningLearning with Large datasets Big Data Set LearningStochastic Gradient descent random gradient descentMini-batch Gradient descent mini batch processing gradient descentConvergence of random gradi

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a collection of information from the online very big Daniel and the machine

machine learning is divided into two types: supervised learning and unsupervised learning . Next I'll give you a detailed introduction to the concepts and differences between the two methods. Supervised Learning (supervised learning): train through an existing training sampl

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a collection of selfless contributions from the online very Daniel and machine

Instructor Xin's Blog is here: Software Engineering Education learned by modern software engineering Then I read the opinions of many students. When I think of High School, the teacher taught me that a good argumentative paper must show my opinion at the beginning. (Well, that's to cope with the college entrance examination. I am far away]. However, in my opinion,Not totally agreeThe opinions of instructors and some students. Over-emphasized"XI"Proportion,I have different opinions.. What did i

Generate Learning AlgorithmsThis course outline:1. Generate learning Algorithms2. Gaussian discriminant analysis (Gda,gaussian discriminant)- Gaussian distribution (brief)- Contrast Generation learning Algorithm discriminant Learning Algorithm (brief)3. Naive Bayes4. Laplace SmoothingReview:Classification algorithm: G

A bunch of online searches, and finally the links and differences between these concepts are summarized as follows: 1. Data mining: Mining is a very broad concept. It literally means digging up useful information from tons of data. This work bi (business intelligence) can be done, data analysis can be done, even market operations can be done. Using Excel to analyze the data and discover some useful information, the process of guiding your business through this information is also the process of

　　Originally this article is prepared for 5.15 more, but the last week has been busy visa and work, no time to postpone, now finally have time to write learning Spark last part of the content.第10-11 is mainly about spark streaming and Mllib. We know that Spark is doing a good job of working with data offline, so how does it behave on real-time data? In actual production, we often need to deal with the received data, such as real-time machine

Learning OpenCV learning notes series (3) display pictures and videos, opencv learning notes OpenCV is a computer vision library, so there are only two objects to process: "Images" and "videos" (in fact, videos are also extracted into single-frame images for processing. In general, or image processing ). To learn OpenCV, you must first know how OpenCV opens the "

How to evaluate the assumptions we get from our learning algorithms and how to prevent overfitting and less-fitting problems.When we determine the parameters of the learning algorithm, we consider the choice of parameters to minimize the training error. Some people think that getting a small training error must be a good thing. But in fact, just because this hypothesis has a very small training error, when

In the words of Russian MYC although is engaged in computer vision, but in school never contact neural network, let alone deep learning. When he was looking for a job, Deep learning was just beginning to get into people's eyes. But now if you are lucky enough to be interviewed by Myc, he will ask you this question Deep Learning why call Deep

This afternoon, idle to nothing, so Baidu turned to see the recent on the pattern recognition, as well as the latest progress in target detection, there are a lot of harvest!------------------------------------AUTHOR:PKF-----------------------------------------------time:2016-1-20--------------------------------------------------------------qq:13277066461. The nature of deep learning2. The effect of deep learning on the detection of traditional transc

Introduction The previous one is about Monte Carlo's reinforcement learning method, Monte Carlo reinforcement Learning algorithm overcomes the difficulty of model unknown to strategy estimation by considering the sampling trajectory, but the Monte Carlo method has the disadvantage that it is necessary to update the strategy after sampling a trajectory every time. The Monte Carlo method does not make full u

CSS learning notes -- learning to locate the position attribute and learning notes position One of the remaining questions before learning today is the position attribute of CSS. First, problems related to position are summarized: The first question: Which of the following attributes does position have? For the positio

Q-learning Source code Analysis.Import Java.util.random;public class qlearning1{private static final int q_size = 6; Private static final Double GAMMA = 0.8; private static final int iterations = 10; private static final int initial_states[] = new int[] {1, 3, 5, 2, 4, 0}; private static final int r[][] = new int[][] {{-1,-1,-1,-1, 0,-1}, { -1,-1,-1, 0,-1, 100}, {-1,-1,-1, 0,-1,-1}, {-1, 0, 0,

Objective:When looking for a job (IT industry), in addition to the common software development, machine learning positions can also be regarded as a choice, many computer graduate students will contact this, if your research direction is machine learning/data mining and so on, and it is very interested in, you can consider the post, After all, machine learning ca

Students in the field of machine learning know that there is a universal theorem in machine learning: There is no free lunch (no lunch). The simple and understandable explanation for it is this: 1, an algorithm (algorithm a) on a specific data set than the performance of another algorithm (algorithm B) at the same time, it must be accompanied by algorithm A on the other specific data set of the performanc

deep understanding of machine learning: Learning Notes from principles to algorithms-1th week 02 easy to get started Deep understanding of machine learning from principle to algorithmic learning notes-1th week 02 Easy to get started 1 General model statistical learning theo

MVC series Learning (16)-area learning, mvc series learning area 1. query the Controller Process 1.1 call controllers in other projects. A. first go to the bin folder under the root directory of the website to traverse all the Assembly B. Find the class ending with Controller C. Find out the class that inherits the Controller D. Create an object wit