Julia Data Mining

Why create a Julia programming language? In a word, because we thirst for knowledge, constant pursuit. We have the core users of MATLAB, there are good at Lisp hackers, Pythonistas and rubyists experts also have a lot; In addition, there are some Perl Daniel, some developers used Mathematica before we had a little understanding of the fur. In other words, they understand more than just the fur, more than others, the development of R language. and C language for us is a deserted island. I ...

Introduction: This article explores the development of the Julia Language and its new features. The author thinks that the birth of a new language is bound to set off a new whirlwind, developers in the enjoyment of it to bring fun while also arguing for its existence value, whether Julia can bring new gospel to developers? Let's go into it together: Why create the Julia programming language? In a word, because we thirst for knowledge, constant pursuit. We have the core users of MATLAB, there are good at Lisp hackers, Pythonistas and Ru ...

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 the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. 　　But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. 　　Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding ...

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

Large data areas of processing, my own contact time is not long, formal projects are still in development, by the large data processing attraction, so there is the idea of writing articles. Large data is presented in the form of database technologies such as Hadoop and "NO SQL", Mongo and Cassandra. Real-time analysis of data is now likely to be easier. Now the transformation of the cluster will be more and more reliable, can be completed within 20 minutes. Because we support it with a table? But these are just some of the newer, untapped advantages and ...

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.