dataquest vs coursera

Mainly for the week content: large-scale machine learning, cases, summary(i) Random gradient descent methodIf there is a large-scale training set, the normal batch gradient descent method needs to calculate the sum of squares of errors across the

This section is about the nuclear svm,andrew Ng's handout, which is also well-spoken.The first is kernel trick, which uses nuclear techniques to simplify the calculation of low-dimensional features by mapping high-dimensional features. The handout

-Cost functionFor linear regression models, the cost function we define is the sum of squares of all model errors. In theory, we can also follow the definition of a logistic regression model, but the problem is that when we bring it into the cost

-Polynomial regressionSince linear regression does not apply to all data, sometimes we need to use curves to fit our data, for example, with two-times polynomial:Or three-time polynomial:Usually we need to look at the data before deciding what model

 Iv. Linear Regression with multiple Variables (Week 2)-Multiple featuresBefore we introduced the Univariate/single feature regression model, we now add more variables to the house price forecast model, which is more features, such as the number

-Unsupervised learningIn supervised learning, whether it is a regression problem or a classification problem, we use the data to have a clear label or the corresponding prediction results.In unsupervised learning, our existing data have no

-Supervised learningFor supervised learning let's look at an example, which is an example of a house price forecast. The horizontal axis of the figure shows the floor space, and the ordinate indicates the price of the house transaction. Each fork in

1. Open FileUse Handle=open (Filename,mode) to open the file. This function will return a handle (which should be translated as "handle") to manipulate the file, and the parameter filename is a string. The parameter mode is optional, ' R ' stands

Autonomous Driving-car Detection Welcome to your Week 3 programming assignment. You'll learn about object detection using the very powerful YOLO model. Many of the "ideas in" notebook are described in the two YOLO et al., Papers:redmon (2016 2640)

Face recognition Face verification vs. face recognition One-Shot LearningFor example, you want to set up a face recognition for the company, but in general, you will not have too many photos of employees, if you follow the previous practice to

Character level language Model-dinosaurus Land Welcome to Dinosaurus island! Million years ago, dinosaurs existed, and in this assignment they is back. You is in charge of a special task. Leading biology researchers was creating new breeds of

ResnetsThe identity blockThe convolutional block (you can use this type of block when the input and output dimensions don ' t match up. The conv2d layer in the shortcut path was used to resize the input xx to a different dimension, so that the

one of the pits in this emojify is that AVG initialization must be (50,) if you use (word_to_vec_map["a"]). Shape just can't live. emojify! Welcome to the second assignment of Week 2. You is going to the use of Word vector representations to

A school that forgets to praise too much and stays in a crowded classroom all day is a poor result. These sites and applications cover countless topics in science, art, and technology. They can teach you to practice any skill, from making red bean paste to using node.js to develop apps, and they're all free. There is absolutely no reason why you should not master a new skill, broaden your knowledge, or ultimately contribute to your career development. You can learn interactively in your own comf

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Programmer Development Guide and programmer Guide A solid foundation in computer science is an important condition for a successful software engineer. This Guide provides programming knowledge learning paths for students who want to enter academic and non-academic fields. You may use this guide to select a course, but ensure that you study the professional course to complete graduation. The online resources provided in this Guide cannot replace your college courses... Instructions for use: 1. Pl

interested in development. The recommendation of a preparatory style Introduction to Computer Science Description: A computer science introduction is the basic content of the introduction of coding.Online resources: Udacity–intro to CS Course, Coursera–computer Science 101 Learn at least one object-oriented programming language: C + +, Java, or Python Beginner Online Resources: Learn to Program:the Fundamentals, MIT I

4 tips on how to use this Learning guide: Please consider your own actual situation to learn. If you still want to learn about other courses outside the guide, go ahead! This guide is for informational purposes only, and there is no guarantee that you will be able to enter Google work even after you have completed all of the courses. This guide is not updated regularly. You can follow Google for Students +page on Google + for more information at any time. The recommen

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