matlab machine learning toolbox

Machine learning system Design (Building machines learning Systems with Python)-Willi Richert Luis Pedro Coelho General statementThe book is 2014, after reading only found that there is a second version of the update, 2016. Recommended to read the latest version, the ability to read English version of the proposal, Chinese translation in some places more awkward

This semester has been to follow up on the Coursera Machina learning public class, the teacher Andrew Ng is one of the founders of Coursera, machine learning aspects of Daniel. This course is a choice for those who want to understand and master machine learning. This course

". There is no photocopy, but it can be down on the Internet. Classics in the classic. Pattern Classification and this book are two must-read books. "Pattern Recognition and machine learning" is very new (07), in Layman's, Shoubushijuan. Finally, on artificial intelligence (especially, decision-making and judgment), we recommend two interesting books,One is "simple heuristics, that makes Us Smart"The o

, requests can fully encapsulate the operation of the protocol stack, the user only care about the real need to send to whom the data sent, which is actually very efficient. And the text operation also saves a lot of things that do not need to be repeated. The temptation of this is very large, although the technical multi-body, but do research to do exploration, time and energy is really valuable, Python saves time to think about the real problem is what we need to solve. In the final analysi

Python and NLTK for Twitter sentiment analysis) Second retry Try: Kernel Sentiment semantic Analysis Plugin in kernel Python (Second attempt: Python Sentiment Analysis) Natural neural Language Processing in every a few Kaggle neural Competition algorithms for Movie Reviews (NLP Natural Language Processing in Movie Reviews related Kaggle Competition) 4. Machine Learning in Python

This paper uses the regularization linear regression model pre-flow (water flowing out of dam) according to the water storage line (water level) of the reservoir, then the Debug Learning Algorithm and discusses the influence of deviation and variance on the linear regression model.① visualizing datasetsThe data set for this job is divided into three parts:Training set (training set), sample matrix (Training Set): X, results label (label of result) Vec

? Crossing, you are a little bit impatient. The angle cosine of the geometry can be used to measure the difference in the direction of two vectors, which is borrowed from the machine learning to measure the difference between sample vectors.(1) The angle cosine formula of vector A (x1,y1) and Vector B (x2,y2) in two-dimensional space:(2) Angle cosine of two n-dimensional sample points a (x11,x12,..., x1n) a

angle? You should be cautious about it. The cosine of the angle in the ry can be used to measure the difference between two vector directions. This concept is used in machine learning to measure the difference between sample vectors. (1) cosine formula of the angle between vector A (x1, Y1) and vector B (X2, Y2) in two-dimensional space: (2) Two n-dimensional sample points A (X11, X12 ,..., X1n) and B (X2

used to measure the difference in the direction of two vectors, which is borrowed from the machine learning to measure the difference between sample vectors.(1) The angle cosine formula of vector A (x1,y1) and Vector B (x2,y2) in two-dimensional space:(2) Angle cosine of two n-dimensional sample points a (x11,x12,..., x1n) and B (x21,x22,..., x2n)Similarly, for two n-dimensional sample points a (x11,x12,..

Machine learning system Design (Building machines learning Systems with Python)-Willi Richert Luis Pedro Coelho General statementThe book is 2014, after reading only found that there is a second version of the update, 2016. Recommended to read the latest version, the ability to read English version of the proposal, Chinese translation in some places more awkward

as:If the covariance matrix is a unit matrix (the independent distribution of each sample vector), the formula becomes:That's the Euclidean distance.If the covariance matrix is a diagonal matrix, the formula becomes the normalized Euclidean distance.(2) The advantages and disadvantages of Markov distance: dimension independent, exclude the interference between the correlations between variables.(3) MATLAB calculation (1 2), (1 3), (2 2), (3 1) of the

direction of two vectors, which is borrowed from the machine learning to measure the difference between sample vectors.(1) The angle cosine formula of vector A (x1,y1) and Vector B (x2,y2) in two-dimensional space:(2) Angle cosine of two n-dimensional sample points a (x11,x12,..., x1n) and B (x21,x22,..., x2n)Similarly, for two n-dimensional sample points a (x11,x12,..., x1n) and B (x21,x22,..., x2n), a co

Reference booksDeep learningDeep learning is a new field in machine learning research, and its motive is to establish and simulate the neural network of human brain import analysis and learning, which imitates the mechanism of human brain to interpret the data.Examples of images, sounds and text. Deep

Coursera Andrew Ng Machine learning is really too hot, recently had time to spend 20 days (3 hours a day or so) finally finished learning all the courses, summarized as follows:(1) Suitable for getting started, speaking the comparative basis, Andrew speaks great;(2) The exercise is relatively easy, but to carefully consider each English word, or easy to make mist

software Matlab and SASS also provide a graphical interface. Personally, I think the software is positioning itself as a software, not a toolkit or a system. But the software is really the first machine learning system with a graphical interface. With the recent years of machine l