Data Science Using Python

R: It's not a real language. Part of the reason we learn about R is that it's not really a programming language. John Cook, an R expert, said: "R is a statistical interactive environment, not a real programming language." It is more helpful to think of R as an interactive environment containing programming languages. "But as Bob Muenchen emphasizes, R is even harder for people who are proficient in SAS and SPSS data tools." About R for analyst ...

Anaconda is the first choice for beginner Python and entry machine learning. It is a Python distribution for scientific computing that provides package management and environment management capabilities to easily handle multi-version python coexistence, switching, and various third-party package installation issues.

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: ...

This article will introduce some practical examples using IPython and pandas for investment analysis and http://www.aliyun.com/zixun/aggregation/10341.html "> Statistical analysis." Let's do a common analysis and you may be able to do it yourself. If you want to analyze stock performance, you can: find a stock in the Yahoo financial zone. Download historical data and save it in CSV file format. Will be CSV ...

The National Aeronautics and Astronautics Research organization NASA has been in deep cooperation with http://www.aliyun.com/zixun/aggregation/13856.html "> Open source Community, and many of its projects have been open source, Special websites have been set up to showcase these projects. Iteye has also recommended some of NASA's Open-source projects. In the following article, we try to overcome the fragmentation and diversity of the open source community, taking NASA and more open source communities as examples to see if they ...

The following small series summarizes 10 best data mining tools for everyone, which can help you analyze big data from various angles and make correct business decisions through data.

Figure http://www.aliyun.com/zixun/aggregation/14345.html "> Data processing in the past has been the patent of data scientists, as the application of data is more and more extensive, large data analysis has become an essential part of the field of data analysis, There is a growing need for easy access to simple graph data analysis tools. Graphlab is a very popular open source project, Graphlab developers are constantly pursuing the innovation and development of graph computing, so that it can cater to a large amount of ...

Open source machine learning tools also allow you to migrate learning, which means you can solve machine learning problems by applying other aspects of knowledge.