A few weeks ago, we discussed advanced copy (modified to the cp command to display the copy progress bar ). One reader pointed out in the comments that other utility not only provides basic cp command functions, but also provides advanced functions not available in cp. Therefore, in this article, we will discuss a very similar command line tool-gcp.Gcp-advanced command line file copyer
According to the operation manual, gcp is an advanced command line
Python detailed process of crawling Coursera course resources, coursera Course Resources
Sometimes we need to add some classic things to our favorites and review them from time to time. Some courses on Coursera are undoubtedly classic. Most of Coursera's finishing courses provide complete teaching resources, including ppt, video, and subtitles. It is very easy to
In Wednesday, we received mass mailings from the Coursera platform, to the effect that Coursera will completely close the Old Course platform on June 30, upgrade to the new course platform, some Old Course resources (course videos, course materials) will not be saved, if you have previously studied the relevant courses, or have the desired courses , Coursera reco
friends, but also hope to get the high people of God's criticism! Preface [Machine Learning] The Coursera Note series was compiled with notes from the course I studied at the Coursera learning (Andrew ng teacher). The content covers linear regression, logistic regression, Softmax regression, SVM, neural networks, and CNN, among other things, and the main learning materials are from the machine lear
Sometimes we need to put some classic things in the collection, always aftertaste, and Coursera on some of the courses are undoubtedly classic. Most of the end courses in Coursera provide a complete set of teaching resources, including PPT, video and subtitles, which will be very easy to learn when offline. Obviously, we will not go to a file to download a file, Only fools do so, programmers are smart!
Wha
! I've been on this course 3 years ago, and it's been a long time ... Before going to bed to see this question, the day before yesterday wrote an article about learning Python in Coursera, just right question, so excerpt part, hope to be helpful:-)
Let's talk about the process of learning Python in Coursera (and recommend this interesting professor, who wants to learn about Python). This is the 0 basic Py
friends leave a message saying they are already charged. Let's go to the official website and check it out! I have taken this course three years ago. It takes a long time ...... I saw this problem before I went to bed. I wrote an article about learning python in coursera the day before yesterday, which is just the right question. So I want to extract some of it and hope it will help me :-)
Next, let's talk about how I learned python on
Operating system Learning notes----process/threading Model----Coursera Course note process/threading model 0. Overview 0.1 Process ModelMulti-Channel program designConcept of process, Process control blockProcess status and transitions, process queuesProcess Control----process creation, revocation, blocking, wake-up 、...0.2 threading ModelWhy threading is introducedThe composition of the threadImplementation of threading mechanismUser-level threads, c
full implementation of multi-layered neural network recognition picture of the cat Original Coursera Course homepage, in the NetEase cloud classroom also has the curriculum resources but no programming practice. This program uses the functions completed in the last job, fully implementing a multilayer neural network, and training to identify whether there is a cat in the picture. There is no comment in the Code and Training test data download Cod
1. What is a special course (specializations)?If you want to learn a major that you do not understand, you can study according to the special course arrangement. Coursera Special Course collects a field of curriculum, and according to the Order of teaching, it is very suitable for the new people who don't feel well.2. Program Design and algorithmThis special course is a computer Foundation course published by Peking University in
(Datasets) data (IRIS)#Exploratory Analysisnames (Iris) head (IRIS)#The following attempts to take Virginica,speal. The method of length is all wrongiris[,2]iris[iris$species=="virginica", 2]mean (iris[iris$species=="virginica", 2])##the above is Error,not correct##tapply (Test$sepal.length,test$species,mean)#using Species.mean to group vectors, this method is feasible, but the above method is necessary to look at the errorLibrary (Datasets) data (Mtcars) #以下为做某个题时的若干测试. And a trial-and-error l
networks and overfitting:
The following is a "small" Neural Network (which has few parameters and is easy to be unfitted ):
It has a low computing cost.
The following is a "big" Neural Network (which has many parameters and is easy to overfit ):
It has a high computing cost. For the problem of Neural Network overfitting, it can be solved through the regularization (λ) method.
References:
Machine Learning video can be viewed or downloaded on Coursera
NTU-Coursera ml: HomeWork 1 Q15-20Question15
The training data format is as follows:
The input has four dimensions, and the output is {-1, + 1 }. There are a total of 400 data records.
The question requires that the weight vector element be initialized to 0, and then "Naive Cycle" is used to traverse the training set. When the iteration is stopped, the weight vector is updated several times.
The so-called "Naive Cycle" means that after an error i
This series is a personal learning note for Andrew Ng Machine Learning course for Coursera website (for reference only)Course URL: https://www.coursera.org/learn/machine-learning Exercise 7--k-means and PCA
Download coursera-Wunda-Machine learning-all programming practice answers
In this exercise, you will implement the K-means clustering algorithm and apply it to compressed images. In the second section, y
Programmers who have turned to AI have followed this number ☝☝☝
Author: Lisa Song
Microsoft Headquarters Cloud Intelligence Advanced data scientist, now lives in Seattle. With years of experience in machine learning and deep learning, we are familiar with the requirements analysis, architecture design, algorithmic development and integrated deployment of machine learning and AI products under various business scenarios.
Wunda Coursera Deep Learni
would the Vectorize this code to run without all for loops? Check all the Apply.
A: v = A * x;
B: v = Ax;
C: V =x ' * A;
D: v = SUM (A * x);
Answer: A. v = a * x;
v = ax:undefined function or variable ' Ax '.
4.Say you has a vectors v and Wwith 7 elements (i.e., they has dimensions 7x1). Consider the following code:
z = 0;
For i = 1:7
Z = z + V (i) * W (i)
End
Which of the following vectorizations correctly compute Z? Check all the Apply.
(w ')Description W over fitting3 Sources of errorNoise, Bias, Variance1. Noise NoiseOf an inherent, irreducible, or reduced nature. 2, Bias Deviation The simpler the model, the greater the deviation The more complex the model, the smaller the deviation3. Variance Variance Simple model, small variance Complex model, large variance Deviations and variance tradeoffs, deviations and variances cannot be calculated Training error and the amount of test data, fixed model complexity, a
-Normal equationSo far, the gradient descent algorithm has been used in linear regression problems, but for some linear regression problems, the normal equation method is a better solution.The normal equation is solved by solving the following equations to find the parameters that make the cost function least:Assuming our training set feature matrix is x, our training set results are vector y, then the normal equation is used to solve the vector:The following table shows the data as an example:T
Week 4 Quizhelp Center
Warning:the hard deadline has passed. You can attempt it, Butyou won't get credit for it. You are are welcome to try it as a learning exercise. In accordance with the Coursera Honor Code, I certify This answers here are I own work. Question 1 Which of the following is nottrue about GFS? The GFS keeps multiple replicas of the same file chunk. The file data transfer happens directly between the GFS client and the GFS chunkservers
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