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Coursera Machine Learning Study notes (ii)

-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

"Python study notes" Coursera's py4e study notes--file

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

Wunda Coursera Deep Learning course deeplearning.ai programming work--autonomous driving-car (4.3)

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)

Coursera Deep Learning Course4 week4

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

Coursera deeplearning Sequence model Week1 Dinosaurus Character level language model

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

Coursera Deep Learning Course4 Week2

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

Coursera Wunda deeplearning.ai Fifth lessons sequence model sequence model second week emofify

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

Coursera Online Learning---section tenth. Large machine learning (Large scale machines learning)

First, how to learn a large-scale data set?In the case of a large training sample set, we can take a small sample to learn the model, such as m=1000, and then draw the corresponding learning curve. If the model is found to be of high deviation

Coursera-machine Learning, Stanford:week 1

Welcome and Introductionoverviewreadinglog 9/9 videos and quiz completed; 10/29 Review; Note1.1 Welcome 1) What are machine learning? Machine learning are the science of getting compters to learn, without being

Coursera Machine Learning Study notes (iv)

 II. Linear Regression with one Variable (Week 1)-Model representationIn the case of previous predictions of house prices, let's say that our training set of regression questions (Training set) looks like this:We use the following notation to

Coursera Public Lesson-machine_learing: Programming 7

This week's programming work is mainly two-part content.1.k-means Clustering.2.PCA (Principle Component analys) principal component analysis.The main method is to compress the image by clustering the image, and then it is found that PCA can compress

Coursera "Machine learning" Wunda-week1-03 gradient Descent algorithm _ machine learning

Gradient descent algorithm minimization of cost function J gradient descent Using the whole machine learning minimization first look at the General J () function problem We have J (θ0,θ1) we want to get min J (θ0,θ1) gradient drop for more general

Coursera Wunda Machine Learning Course Summary notes and work Code-5th week neural network continued

Neural networks:learning Last week's course learned the neural network forward propagation algorithm, this week's course mainly lies in the neural network reverse renewal process. 1.1 Cost function Let's recall the value function of logistic

Coursera Deep Learning Fourth lesson accumulation neural network fourth week programming work Art Generation with neural Style transfer-v2

Deep Learning & art:neural Style Transfer Welcome to the second assignment of this week. In this assignment, you'll learn about neural Style Transfer. This algorithm is created by Gatys et al. (https://arxiv.org/abs/1508.06576). in this assignment,

E-commerce website Commodity Management (i)

?vEpoch Timestamp cluster status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_t IME Active_shards_percent1525610669 20:44:29 elasticsearch Green 1 1 0 0 0 0 0 0 -100%How do you quickly understand the health of your cluster? Green, yellow, red?Green: Primary shared and replica shared are active states for each indexYellow: Primary shared for each index is active, part replica shared is not activeRed: Primary shared that is not an index is active, and some of the

Programmer Development Guide and programmer Guide

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

Go: Google Technology Development Guide: Advice for college students to learn by themselves

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

Google publishes Programmer's Guide

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

Detailed description of the "machine Learning enthusiast" project and its website by Dr. Huanghai

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

Zhihu · shell: Anatomy of survival samples of two knowledge-based communities

cooperate with enterprises, it will lose the credibility on which it depends for a living, and it will be realized through community advertising, it also relies on quantitative changes to cause qualitative changes. This requires a large number of users to be imported, which is contrary to the positioning of high-quality communities. More importantly, with reference to the commercialization process of Tianya community, the article is only made based on an acre of land in an online community. The

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