Personal Summary: 1, this article is mainly proof of the main things, so the mathematical formula is relatively more, the original note author omitted some things, no and the above is very good cohesion, so beginners do not necessarily see clearly, the proposed combination of Stanford machine learning the original handout (English, did not find the full text of the Chinese translation version) to see, If the derivation of the formula is confusing, it
of epsilon items! If the epsilon value is too low, the data after the whitening will appear to be noisy; Conversely, if the epsilon value is too high, the albino data will be too blurry compared to the original data.Epsilon method of selection:A. Draw the eigenvalues of the data graphically; b. Select a characteristic value that is larger than most of the noise in the data to reflect the epsilon .2. How to adjust the epsilon specifically? I don't know, if I had a exercise, I'd be fine.2. When p
This is the essay of Mehran Sahami, professor of Open Class: Programming Methodology at Stanford University, which is open to NetEase.Currently only see the third class, "Karel and Java", my harvest has the following points:1. Software engineering is different from normal writing code. Software should consider a lot of things, such as portability, easy to upgrade maintenance, and so on, not just write code to implement the function as simple.2. The co
It is decided that machine learning is under system learning, and Stanford courseware is the main line.
Notes1 is part of the http://www.stanford.edu/class/cs229/notes/cs229-notes1.pdf about Regression 1. Linear Regression
For example, if the House Price is predicted and the data cannot be found on the Internet, use five data points for the experiment.
House.txt, 5 data records, number of bedrooms, Price.
Area bedrooms price2104 3 4001600 3 330
I am honored to attend the graduation ceremony with you today. Stanford is one of the best universities in the world. I have never graduated from college. To be honest, today may be the last day of my life before I graduated from college. Today, I want to tell you three stories in my life. It's not a big deal. It's just three stories.
The first story is about how to connect the dots in your life.
I dropped out after six months at Reed University, but
CNET Technology Information Network January 16 International report Stanford University researchers have a major discovery, laptop battery charging once can run for a day or longer.
Researchers have discovered a way to increase the battery of lithium-ion battery storage by 10 times, possibly extending the battery life of a laptop from the current 4 hours to 40 hours.
The new battery was developed by Yi Cui, a TA, and colleagues from the Department
NPL STANFORD-4.NPL with DL
@ (NPL) [Read Notes]
NPL STANFORD-4NPL with DL starting from a neuron feedforward computation of single layer neural network Maximum Margin objective Function Reverse propagation backpropagation
1. Start with a neuron
A neuron is the most basic component of a neural network that receives n inputs and produces a single output. The different neurons have different parameters (or we
Stanford cs231n 2017 newest Course: Li Feifei Detailed framework realization and comparison of depth learning by Zhuzhibosmith June 19, 2017 13:37
Stanford University Course cs231n (convolutional Neural Networks for visual recognition) is widely admired in academia as an important foundation course in depth learning and computer vision. This April, cs231n again, the new cs231n Spring 2017 is still led by Li
1. IntroductionStanford participle currently supports Arabic and Chinese. Its principle is based on crfs, crfs participle principle is not difficult to understand, that is, the word segmentation as another form of named entity recognition, the use of features to establish a probability map model, with the VETERBI algorithm to find the shortest path. Stanford NLP provides the source demo, the current version is 3.5.2. : http://nlp.stanford.edu/softwar
Summary of the Open course for IOS development at Stanford UniversityObjectiveThe most famous tutorial on iphone development is the "Open iphone Development Course" released by Stanford University. This public course, formerly known as the IPhone Development tutorial, was introduced this year due to the popularity of tablets, and has also been added to the ipad development-related curriculum. In the NetEase
) { performseguewithidentifier ("Nothing", Sender:nil) }You can see that we let sender for nil delegate Click on this button to do nothing, but it will still execute to the Prepareforsegue method, at this time we add a case in the Prepareforsegue method:Case ' nothing ': hvc.happiness = 25Run you'll find the Nothing button still works.So why do we use segue in our code, and you might want to determine which segue to use based on some state after the button is clicked, which is a classi
can do some global operations in these proxy methods.If you have a phone call when you use the app, the app pauses and the status moves from active to inactive.From active to inactive such as when your app loads successfully, it calls the method above and loads applicationdidbecomeactive (uiapplication) When your app becomes inactive from inactivity. This proxy method and the Pause proxy method above are a pair. You can use uiapplicationdidbecomeactivenotification this station.The following pro
UITableViewCell, You can then use the UITableViewCell API: For a custom cell: The same is true with identifier, and the difference is that you need to convert the type to the type it needs, and then use the APIs in the subclass: Except cellfor ... This method, take a look at the other two methods in DataSource: Section has a default value of 1, you do not override this method, the number of sections will be set to 1. But the number of row does not have a default value, so you must override this
in the parameters of the Nsfetchrequest type, you can set the query request to query the data in the database, get the return value of Nsarray type, the member type is nsmanagedobject. This is what you can do with the database. Once you have these Nsmanagedobject objects, you can use both methods: SetValue and Valueforkey to manipulate the object, or to create a subclass of NSObject, usually with the same name as the entity in the database: class Photo:NSObject {@NSManagedtitle:String}Then use
interacts with some data without returning any information, such as adding a new contact, and if you need to, you can interact with unwind segue, but most modal MVC will only dismiss (remove) themselves. So how to remove it? If you use unwind, the current controller is automatically removed when you return to the specified controller. If you do not apply unwind, you need to call dismiss, call the following method: dismissviewcontrolleranimated, and then return to the previous MVC (that is, MVC
animations is to set the MyView to full transparency. The meaning of the first parameter 3.0 is that the transparent process will be completed in 3 seconds, the second parameter 2.0 meaning that the animation will delay 2S. The third parameter options are used in all animation methods, which is an enumeration that indicates different types of animations, which are described later.Animations is what we need to do, completion is the completion of the operation, just see in the definition of the c
learning combat" in p82-83 gives an improved strategy, the learning rate is gradually declining, but not strictly down, part of the code is: For J in Range (Numiter): For I in range (m): alpha = 4/(1.0+j+i) +0.01 so Alpha decreases 1/(j+i) every time, and when J 3. Can the random gradient drop find the value that minimizes the cost function? Not necessarily, but as the number of iterations increases, it will hang around the optimal solution, but this value is sufficient for us, and machine lear
in x:A. f (x) = a + b^2xB. The discriminant function from LDA.C. \delta_k (x) = x\frac{\mu_k}{\sigma^2}-\frac{\mu_k^2}{2\sigma^2} +\log (\pi_k)D. \text{logit} (P (y = 1 | x)) where p (y = 1 | x) is as in logistic regressionE. P (y = 1 | x) from logistic regressionCorrect answer:eP(y=1|x)">explanation:p (y = 1 | x) from logistic regression are not linear because it involves both an exponential function of X and a ratio. f(x)=a+b2x">5.1 R2 What is reasons why test error could is less than trainin
mathematical expression was unfolded using Taylor's formula, and looked a bit ugly, so we compared the Taylor expansion in the case of a one-dimensional argument.You know what's going on with the Taylor expansion in multidimensional situations.in the [1] type, the higher order infinitesimal can be ignored, so the [1] type is taken to the minimum value,should maketake the minimum-this is the dot product (quantity product) of two vectors, and in what case is the value minimal? look at the two vec
invoking the example in MATLAB above, we can define the cost function of the logistic regression as follows:In the figure, Jval represents the cost function expression, where the last item is the penalty for the parameter θ; The following is a gradient of the derivation of each θj, where θ0 is not in the penalty, so gradient is not changed, and Θ1~θn has one more (λ/m) *θj respectively;At this point, regularization can solve the linear and logistic overfitting regression problem ~
The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion;
products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the
content of the page makes you feel confusing, please write us an email, we will handle the problem
within 5 days after receiving your email.
If you find any instances of plagiarism from the community, please send an email to:
info-contact@alibabacloud.com
and provide relevant evidence. A staff member will contact you within 5 working days.