R For Machine Learning

Which of the following 5 languages are NODE, LUA, Python, Ruby, R, and which will be better applied in the 2014? I don't hesitate to choose R. 　　R is not only 2014, but also the protagonist for a longer period of time. 1. My programming background programmer, Architect, from the beginning of programming to today, has been convinced that Java is the language to change the world, Java has done, and has been very brilliant. But when the world of Java is becoming bigger and larger, when it becomes omnipotent, it is not professional enough for other languages to develop ...

Introduction: It is well known that R is unparalleled in solving statistical problems. But R is slow at data speeds up to 2G, creating a solution that runs distributed algorithms in conjunction with Hadoop, but is there a team that uses solutions like python + Hadoop? R Such origins in the statistical computer package and Hadoop combination will not be a problem? The answer from the king of Frank: Because they do not understand the characteristics of R and Hadoop application scenarios, just ...

R is a GNU open Source Tool, with S-language pedigree, skilled in statistical computing and statistical charting. An open source project launched by Revolution Analytics Rhadoop the R language with Hadoop, which is a good place to play R language expertise. The vast number of R language enthusiasts with powerful tools Rhadoop, can be in the field of large data, which is undoubtedly a good news for R language programmers. The author gave a detailed explanation of R language and Hadoop from a programmer's point of view. The following is the original: Preface wrote several ...

C + + computer vision ccv-based on C language/provides cache/core machine Vision Library, novel Machine Vision Library opencv-It provides C + +, C, Python, Java and MATLAB interfaces, and supports Windows, Linux, Android and Mac OS operating system. General machine learning Mlpack dlib Ecogg Shark Closure Universal machine learning Closure Toolbox-cloj ...

With large data being adopted by more enterprises, the compilation and production language of data processing and analysis algorithms have been widely concerned. and unknowingly, open source statistics language R has become a basic technology for large data scientists and developers. 　　In all programming languages and techniques, popularity has soared. The following is the translation through the integration with the large data processing tools, R provides the depth statistical capability of large datasets, including statistical analysis and data-driven visualization. In industries such as finance, pharmaceuticals, media, and sales, which can directly take decisions from data, R has been applied in depth. ...

Why let Hadoop combine R language? R language and Hadoop let us realize that both technologies are powerful in their respective fields. Many http://www.aliyun.com/zixun/aggregation/7155.html "> developers will ask the following 2 questions at the computer's perspective. 　　The problem 1:hadoop family is so powerful, why do you want to combine R language? Problem 2:mahout can also do data mining and machine learning, ...

Machine learning is a multi-disciplinary subject that has emerged in the past 20 years and involves many disciplines such as probability theory, statistics, approximation theory, convex analysis, and computational complexity theory.

Machine Learning (ML) studies these patterns and encodes human decision processes into algorithms. These algorithms can be applied to several instances to arrive at meaningful conclusions.

Machine learning engineers are part of the team that develops products and builds algorithms and ensures that they work reliably, quickly, and on a scale.

Computing is often used to analyze data, while understanding data relies on machine learning. 　　For many years, machine learning has been very remote and elusive to most developers. This is probably one of the most profitable and popular technologies now. 　　No doubt--as a developer, machine learning is a stage that can be a skill. Figure 1: Machine Learning composition machine learning is a reasonable extension of simple data retrieval and storage. 　　By developing a variety of components to make the computer more intelligent learning and behavior. Machine learning makes digging history count ...