coursera cs50

-Cost functionFor the training set and our assumptions, we will consider how to determine the coefficients in the assumptions.What we are going to do now is to choose the right parameters, and the selection of parameters directly affects the

Vi. Logistic Regression (Week 3)-ClassificationIn the classification problem, what we try to predict is whether the result belongs to a certain class (for example, correct or error). Examples of classification problems include determining whether an

Anomaly Detection and Recommender SystemsThis week's programming job is divided into two parts: anomaly detection and referral system.Anomaly Detection: The essence is to use the Gaussian distribution of the sample to the special value to estimate

The origin of Neural network Considering a nonlinear classification, when the number of features is very small, the logical regression can be completed, but when the feature number becomes larger, the higher order term will be exponential growth,

Building your recurrent neural network-step by step Welcome to Course 5 ' s-A-assignment! In this assignment, you'll implement your The recurrent neural network in NumPy. Recurrent neural Networks (RNN) are very effective for Natural Language

The recent Wunda study of the five-door sequence model finally came out, I took some time, just completed the course, I have to say, Ng's fifth Class I am still very satisfied with the video and the work is very good, the job content is also very

1. How to become a better learner metaphor and analogy helps to learn without jealousy genius 1. How to become a better learner the biggest gift for your brain is exercising more. we used to think that the brain was basically stereotyped after

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

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

 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

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

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

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

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,

Mini-project Description-rock-paper-scissors-lizard-spockRock-paper-scissors is a hand game this is played by the people. The players count to three in unison and simultaneously "throw" one of the three hand signals this correspond to rock, paper O

Mini-project description-"Guess the number" gameOne of the simplest two-player games is "Guess the number". The first player thinks of a secret number in some known range while the second player attempts to guess the number. After each guess, the

1. Open the URL https://www.coursera.org Register, then search for the course you want to study, no certificate is required for free2. If the video has been buffered or displays a black screen, you need to modify the

This section mainly reviews some simple knowledge about linear algebra.Matrix and vector Matrix Number of $ m \ times N $ A _ {IJ} (I = ,..., m; j = 1, 2 ,..., n) $ the number table of $ M $ row $ N $ column, which is called the matrix of $ M $ row $

Mainly for the sixth week Content machine learning application recommendations and system design.What to do nextWhen training good one model, predicting unknown data discovery, how to improve it? Get more examples of training Try to

In this section, a linear model is introduced, and several linear models are compared, and the linear regression and the logistic regression are used for classification by the conversion error function.More important is this diagram, which explains