machine learning course on coursera

front-end experience joined our team that we fixed the problem and made our own decision.The lesson of this problem is: to build a team to be more cautious, from a more systematic perspective , can not say that machine learning only recruit algorithm engineers, this will lead to team-level short board, for some problems buried foreshadowing.However, some problems may be difficult to predict before they are

training set for training and get different model; 4, the model on the CV set on the performance of a score, choose a better performance models; There is a need to note that we will eventually choose to perform the best model on the CV set, but the final evaluation of this model is to be in a new data d_test (similar to the Netflix Prize competition, The official eventually gives your model a rating of data) on the test. Andrew NG recommends dividing the data as follows: k-fold Cross validtio

the output4) due to random sampling, the variance of the trained model is small and the generalization ability is strong.5) The algorithm is easier to implement than boosting.6) Insensitive to partial feature deletionsMain disadvantages of random forests:1) In some large noisy sample sets, the RF model is prone to fall into the fit2) The characteristics of the value ratio are easy to influence the decision of random forest, and affect the fitting effect of the model.Finally, on the bagging focu

Tags: get attention to bin www. Command line nbsp PAC Read Write codeRecently began to look at Coursera above the machine learning course, the above mentioned a software--octave, so I transferred the following blog.Do not know what is the specific reason, I download octave-4.2.1-w64-installer.exe, the speed is extremel

, linear algebra library to accelerate the calculation, the smaller batch, the acceleration effect may be less obvious. Of course, batch is not the bigger the better, too big, the weight of the update will be less frequent, resulting in the optimization process is too long. So mini-batch size, not static, according to your data set size, your device computing ability to choose. The the-Go is therefore-use some acceptable (but not necessarily-

Hello everyone, I am mac Jiang. See everyone's support for my blog, very touched. Today I am sharing my handwritten notes while learning the cornerstone of machine learning. When I was studying, I wrote down something that I thought was important, one for the sake of deepening the impression, and the other for the later review.Online

of the most important aspects of machine learning is regularization and regularization, which will be detailed in subsequent chapters. Here is an intuitive understanding. The most common regularization item is the model of the constraint parameter. The following formula is used to constrain W: If y is a linear equation, the formula (1.4) is ridge regression. In Figure 1.7, we can see that the changed v

and regularization, which will be detailed in subsequent chapters. Here is an intuitive understanding. The most common regularization item is the model of the constraint parameter. The following formula is used to constrain W: If y is a linear equation, the formula (1.4) is ridge regression. In Figure 1.7, we can see that the changed value can have a huge impact on the model. When M = 9 is still used, it can be better fitted by adding it to the regularization item. Of

(SVM) training algorithm can be classified into one of two categories after being entered into a new case, making itself a non-probabilistic binary linear classifier.The SVM model represents the training cases as points in space, which are mapped to a picture, separated by an explicit, widest possible interval to differentiate between two categories.Algorithm explanation: Support vector machine for machine

Machine learning Algorithms Study NotesGochesong@ Cedar CedroMicrosoft MVPThis series is the learning note for Andrew Ng at Stanford's machine learning course CS 229.Machine

Turn from: 11900000053568571. PrefaceOriginally this title I think is 算法工程师的技能 , but I think if added in the 机器学习 title, the estimated point of people will be a little more, so the title into this, hehe, and is indexed by the search engine when a more popular words, estimated exposure will be more points. But rest assured, the article is not tricky, we are serious.Today, the 机器学习 last two years of the computer field of the hottest topic, this is not a machin