udacity machine learning course

co-authored encyclopedia-style textbooks, not only in the field of numerical computing in detail, but also comes with high-quality source code, a lot of programs can be directly used. Of course, the book is very thick (1000+), but after reading through it should basically be able to deal with most of the problems encountered in the work of the numerical calculation.Gene H. Golub "Matrix computation"This should be done without too much introduction to

1. Background 1.1 questionsIn the practical application of machine learning, the number of features may be more, in which there may be irrelevant features, there may be correlations between features, easy to lead to the following consequences:(1) The more the number of features, the more time it takes to analyze features and train the model, the more complex the model will be.(2) The more the number of feat

. However, there is a better neural network model, which is the restricted Boltzmann machine. The method of using Cascade Boltzmann machines to form deep neural networks is called deep belief network DBN in deep learning, which is a very popular method at present. In the following terms, the self-associative network is called the Self-coding network Autoencoder. By cascading the deep network of self-coded n

Original address: http://www.csuldw.com/2016/02/26/2016-02-26-choosing-a-machine-learning-classifier/This paper mainly reviews the adaptation scenarios and the advantages and disadvantages of several common algorithms!Machine learning algorithm too many, classification, regression, clustering, recommendation, image rec

analyzing the difference between the train set and the dev set, we try to get more train set accumulated by the dev set distribution. The method of synthesizing artificial data is used. For example, in the car voice recognition system, training set for quiet environment recorded in 10,000 hours of voice data, but the actual application, the car voice recognition system input voice data is included noise, such as the car sent sound, the surrounding vehicle horn sound, car echo and so on. So,

discrete is the n value, then after crosses will have the m*n variable, further introduces the nonlinearity, the enhancement expression ability; 5, the characteristics of the discretization, the model will be more stable, such as if the user age discretization, 20-30 as an interval, not because a user aged one year old to become a completely different person. Of course, the sample in the adjacent area is just the opposite, so how to divide the interv

It seems that mathematics is always not enough. These days, in order to solve some problems in research, we held a textbook on mathematics in the library. From the university to the present, the number of Mathematics Courses in the classroom and the number of self-taught mathematics courses is not very small. However, during the study, we always find that new mathematical knowledge needs to be supplemented. Learning and vision are the intersection of

What are the features of Python that make scientific computing developers so fond of them? Reply content: Summary: Good writing, support comprehensive, good tune, speed is not slow. 1. Python is the language of interpretation, which makes it easier to write a program. For example, in a compiler language such as C, write a matrix multiplication, you need to allocate the operand (matrix) of memory, allocate the results of memory, manually call the Blas interface Gemm, and finally if the use of s

Python machine learning-sklearn digging breast cancer cells (Bo Master personally recorded)Https://study.163.com/course/introduction.htm?courseId=1005269003utm_campaign=commissionutm_source= Cp-400000000398149utm_medium=shareCourse OverviewToby, a licensed financial company as a model validation expert, the largest data mining department in the domestic medical d

Statement: This article usesVirualboxThe Virtual Machine System is used as an example to build a learning environment for learners.VirtualboxRemote connection. If you have better suggestions, leave a message. To learn, you need a good learning environment. This article uses a virtual machine as an example to build

Course Description:??The course style is easy to understand, real case actual cases. Carefully select the real data set as a case, through the Python Data Science library Numpy,pandas,matplot combined with the machine learning Library Scikit-learn to complete some of the column mac