microburst learning

After tossing the crawler and some interesting content, I recently in the R language for simple machine learning knowledge, the main reference is "machine learning-Practical Case Analysis" this book.This book is a rare, purely r language-based machine learning knowledge, covering 11 cases. Divided into 12 chapters. Both the author's notes and the code sections ar

I find myself coming back to the same few pictures when explaining basic machine learning concepts. Below is a list I find most illuminating.1. Test and Training error: Why lower training error was not always a good thing:esl figure 2.11. Test and training error as a function of model complexity.2. Under and overfitting: PRML figure 1.4. Plots of polynomials has various orders M, shown as red curves, fitted to the data set generated by the green curve

http://blog.csdn.net/pipisorry/article/details/44119187Machine learning machines Learning-andrew NG Courses Study notesMachine Learning System DesignPrioritizing what do I do on priorityError analysisError Metrics for skewed Classes Error metrics with biased classesTrading Off Precision and recall weigh accuracy and recall rateData for machines

Chapter One introduction to Deep learning 1. Artificial sometimes not very good to extract the characteristics of the entity, then there is an automatic way. Yes, one of the key problems in the deep learning solution is to automatically combine simple features into more complex features and use these combination features to solve problems. 2. Depth learning is a

In order to you can better learn PHP, this time mainly want to talk about the PHP learning line, carding each stage of the PHP Programmer's technical requirements, according to their own situation to set the learning growth goal. Learning lines and advice for beginners in PHP We want to have a gradual learning process

Recommended AngularJS interactive learning courses and AngularJS Learning Courses0. Directory Directory Preview Details 1 Learn Angular 2 AngularJS getting started tutorial Perception Statement 1. Preview If you are in a hurry and do not have time to listen to my nonsense, you can directly read the two AngularJS interactive learning tutorials

At present, the application of machine learning business is more in communication and finance. Large data, machine learning these concepts have been popularized in recent years, but many researchers have worked in this field more than 10 years earlier. Now finally ushered in their own tuyere. I will use the professional experience of millions of machine-learning

ECCV-2010 Tutorial:feature Learning for Image classification OrganizersKai Yu (NEC laboratories America, [email protected]),Andrew Ng (Stanford University, [email protected])Place Time: Creta Maris Hotel, Crete, Greece, 9:00–13:00, September 5th, 2010 Course Material and Software The quality of visual features is crucial for a wide range of computer vision topics, e.g., scene classification, OBJEC t recognition,

I. BACKGROUND In machine learning, there are 2 great ideas for supervised learning (supervised learning) and unsupervised learning (unsupervised learning) Supervised learning, in layman's terms, is you know the answer to the quest

IOS Internal learning-Beginner 1, ios Internal learning Hesitated for a long time. A year ago, I switched from j2ee to android. Because android is almost supported by the java language. As a result, I learned how to use the basic functions of Android in a month. In the second month, we began to develop a series of projects It is a mobile computer nanny, shopping in China, and jiadobao activity app. I gradua

you to someone.Daughter: How old are you?Mother: 26.Daughter: Long handsome not handsome?Mother: Very handsome.Daughter: Is the income high?Mother: Not very high, medium condition.Daughter: Is it a civil servant?Mother: Yes, I work in the Inland Revenue Department.Daughter: Well, I'll meet you.Use decision trees to represent:As a code farmer often will constantly knock if, else if, else, in fact, has been used in the decision tree thinking. Just have you ever thought, there are so many conditio

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job four q13-20 MATLAB implementation. The previous code was implemented through C + +, but found that C + + implementation of the code is too cumbersome, the job also to change the parameter values frequently, so choose to use MATLAB to achieve. Compared with C + +, Matl

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job four q13-20 MATLAB implementation.Once the code is implemented through C + +. However, it is too cumbersome to discover that C + + implements this code. This job also need to change the number of participants frequently, so choose to use MATLAB to achieve. Compared to

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 learning parameters, the optimization algorithm b

We have developed a false news detector using machine learning and natural language processing, which has an accuracy rate of more than 95% on the validation set. In the real world, the accuracy rate should be lower than 95%, especially with the passage of time, the way the creation of false news will change. Because of the rapid development of natural language processing and machine learning, I thought may

Last content: Model-free Control. The so-called model-free refers to the absence of a given MDP (that is, MDP is unknown, not even the MDP process). It is hoped that the control is not given in the case of MDP (ideally the policy is not given, optimise the value function of an unknown MDP). Model-free control has two main methods: On-policy learning and Off-policy learning; On-policy

Machine learning is a comprehensive and applied discipline that can be used to solve problems in various fields such as computer vision/biology/robotics and everyday languages, as a result of research on artificial intelligence, and machine learning is designed to enable computers to have the ability to learn as humans do, because we find that computers have the functions to accomplish, Can not be achieved

Today finally the basic knowledge of OC finished, but these knowledge is the most basic, there are a lot of high-level knowledge, this may need to learn slowly behind to understand. The following is the study of the directory of OC Tutorial, if you find that there is something wrong place, please correct me, younger brother is a freshman, more please OC veteran to spray ~ ~1.---Overview of OC Learning articles2, OC Study---The first program HelloWorld

Enhanced Learning (reinforcement learning and Control) [PDF version] enhanced learning. pdfIn the previous discussion, we always given a sample x and then gave or didn't give the label Y. The samples are then fitted, classified, clustered, or reduced to a dimension. However, for many sequence decisions or control problems, it is difficult to have such a regular s

Enhanced Learning (reinforcement learning and Control) [PDF version] enhanced learning. pdfIn the previous discussion, we always given a sample x and then gave or didn't give the label Y. The samples are then fitted, classified, clustered, or reduced to a dimension. However, for many sequence decisions or control problems, it is difficult to have such a regular s