statistics and machine learning toolbox

"Statistical learning theory" PDFVapnik's masterpiece, the authority of the statistical academia, this book to the theory to the philosophical level, his other book "The Nature Ofstatistical Learning theory" is also a rare statistical study of good books, but these two books are relatively deep, Suitable for readers with a certain foundation. Fundamentals of Mathematics Matrix Analysis PDF246Roger H

Machine learning goals: Let machines learn to complete tasks through several instances. Statistics is a field that machine learning experts often study. The machine learning method is n

Spark. Although it is Java, the library and platform also support binding Java, Scala and Python. This library is up-to-date and has many algorithms. 22. H2O is a machine learning API for smart applications. It scales statistics, machine learning, and mathematics on big dat

often exchange positions with nouns, so no matter how well the word order is remembered, it will not make the output better. Therefore, Model 4 takes into account the so-called "relative order"--if two words are always swapped for positions, the models can learn.Model 5: Fix ErrorsThere's nothing new here. Model 5 has more parameters to learn, and it fixes the problem of word position conflict.Although word-based systems are inherently revolutionary, they still cannot handle lattices, sex, and

estimate the intensity of change of a function f near his expectation. It is defined If the variable X itself is considered, the variance of X is also available: Note: (skipped in the book) This equation is actually derived from the definition of variance: In addition, we define two random variables.Covariance: It indicates the degree to which x and y change together. If X and Y are independent of each other, the covariance is 0. We can see that the variance of a single var

learning theory and application, MIThttp://dataiap.github.com/dataiap/Data Literacy, MIThttps://wiki.engr.illinois.edu/display/cs412 Data Mining, UIUChttp://work.caltech.edu/telecourse.html data, California Institute of Technology Studyhttp://itunes.apple.com/us/itunes-u/statistics-110-introduction/id495213607 Statistical Introduction, Harvard University, USAHttp://www.umiacs.umd.edu/~jimmylin/cloud-2010-S

, regression (there are already many statistical knowledge can be used), structural learning (can be understood as a complex multi-classification problem, such as natural language processing of the problem of part-of-speech tagging, due to indefinite sentence length, the category may have infinite variety) The third lecture has not been finished, the back again said:Batch Learning v.s Online

On Github, Afshinea contributed a memo to the classic Stanford CS229 Course, which included supervised learning, unsupervised learning, and knowledge of probability and statistics, linear algebra, and calculus for further studies. Project Address: https://github.com/afshinea/stanford-cs-229-machine-learningAccordi

learning API for smart applications. It has scaled statistics, machine learning, and mathematics on big data. H2O can be extended, and developers can use simple mathematical knowledge in the core section.Walnutiq is a part of the human brain object-oriented model, with a common theory of

, statistical distribution, and model convergence diagnostic tools, as well as some hierarchical models. If you want to perform Bayesian analysis, you should take a look.Shogun Shogun1 is a machine learning toolbox focusing on Support Vector Machines (SVM). it is written in C ++. It is under active development and maintenance. It provides Python interfaces and is

First, the visualization method Bar chart Pie chart Box-line Diagram (box chart) Bubble chart Histogram Kernel density estimation (KDE) diagram Line Surface Chart Network Diagram Scatter chart Tree Chart Violin chart Square Chart Three-dimensional diagram Second, interactive tools Ipython, Ipython Notebook plotly Iii. Python IDE Type Pycharm, specifying a Java swing-based user interface PyDev, SWT-based

. H2O is a machine learning API for intelligent applications. It has scaled up statistics, machine learning and mathematics on large data. H2O can be extended, and developers can use simple mathematical knowledge in the core section. Walnutiq is an object-oriented model of t

other. Expand your Reading (English): What is a data scientist with a unicorn type? : Do not know why now what "unicorn" type of this concept will be so popular, enterprises also love to call Unicorn, the industry also called Unicorn. But why a unicorn, I first thought of the wizard series game. (Cover face ~) Top Data Analytics tools for business: Ten tools for commercial analysis, highly recommended!!! Data science:bridging the Business IT Gap: The second part of the m

: Variance: Variance can be used to estimate the intensity of change of a function f near his expectation. It is defined If the variable X itself is considered, the variance of X is also available: Note: (skipped in the book) This equation is actually derived from the definition of variance: In addition, we define two random variables.Covariance: X, YDegree of change together, if XAnd yIndependent of each other, the covariance is 0. We can see that the variance of a s

. Although neither the categories nor the algorithms are exhaustive, I think they are representative and contribute to a general understanding of the whole field.Regression analysis　　Regression is a modeling method that determines the amount of prediction errors for a model, and then iteratively optimizes the relationship between the variables by this amount. Regression method is the main application of statistics, which is classified as statistical

Content Summary The main content of this blog is:1. Model Selection2. Bayesian statistics and Regulation (Bayesian statistics and regularization) The core is the choice of the model, although not so many complex formulas, but he provides more macro guidance, and many times is essential. Now let's begin model selection Suppose we train different models to solve a learni