advanced machine learning coursera

Dialogue machine learning Great God Yoshua Bengio (Next)Professor Yoshua Bengio (Personal homepage) is one of the great Gods of machine learning, especially in the field of deep learning. Together with Geoff Hinton and Professor Yann LeCun (Yan), he created the deep

Hello everyone, I am mac Jiang, today and everyone to share Coursera-stanford university-machine Learning-week 10:large scale machine learning after the class exercise solution. Although my answer passed the system test, but my analysis is not necessarily correct, if you bo

Part I: ClassificationThe first two parts of the book focus on supervised Learning (supervisedieaming). In the process of supervising learning, we only need to give the input sample set , and the machine can push the possible results of the specified target variable from it. Supervised learning is relatively simple, an

and theories, especially for those who do engineering applications, the real need for mathematical knowledge mediocre, mainly include: calculus, linear algebra, probability theory, optimization methodLet's take a look at the following:CalculusFirst of all, Calculus/advanced mathematics. In machine learning, calculus is mainly used in the differential part, the f

values of each eigenvalue have the same scale range, so that the influence of each eigenvalue is the same.How do I set the value of λ? By selecting a different λ to repeat the test process, a λ that minimizes the prediction error is obtained. The best value can be obtained by cross-validation-the sum of squared errors is minimized on the test data.Ridge regression was first used to deal with more than a sample number of features, and is now used to add human bias to the estimate, thus obtaining

these friends are connected to you ). From the above example, we can see that machine learning is actually a imitation of human intelligence and the only way to achieve human and higher intelligence. (What are these items ?) What does he have in general? (Difficult machine learning theory, mathematics) Part 1: underl

actually nearly 20000 citations, really scary. It is not surprising to think carefully, all kinds of research work, as long as the classification, most will use the SVM algorithm or with SVM algorithm comparison, and at this time LIBSVM is often the preferred tool. In fact, not only the academia, LIBSVM in the industrial sector also has a very wide range of applications. This is due to the stability and efficiency of the algorithm implementation, on the other hand because LIBSVM provides a rich

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

Alea.cubase to performENCOG-Advanced neural networks and machine learning frameworks, including classes used to create multiple networks, and classes that support the need for data regulation and processing in neural networks; its training uses multi-threaded elastic propagation; it also uses GPUs to speed up processing time; it provides a graphical interface to

make an overall prediction. This kind of algorithm is also called meta-algorithm (META-ALGORITHM). The most common ideas for integration are two bagging and boosting.boostingBuild new classifiers and integrate them based on error-boosting classifier performance by focusing on samples that have been categorized incorrectly by existing classifiers.BaggingClassifier construction method based on random resampling of data.Algorithm Example: Boosting bootstrapped Aggregation (Bagging)

1. Foreign Tutorial website Android Developers Blog Don't explain Vogella Very good site, free, including Android tutorials are more comprehensive, and the tutorial often quoted Daniel Blog, there will be a lot of unexpected discoveries. Code resources are available, but not very easy to find. Very recommended Tutorialspoint Perfect for getting started, providing basic all the basics of tutorials,

are pros and cons. This also gives us a large part of the time to explore.I began to develop a learning plan, collect information, watch the video, hope to understand these things in theory, slowly to practice them, and finally use. Well, it looks good. The idea is really hardships, and I finally failed to make it through the road. Theoretical knowledge involves, probability theory, Mathematical statistics, advan