Python is an object-oriented, literal translation of computer programming language. The python syntax is simple and clear, with a rich and powerful class library. Python's design insists on a clear and uniform style, making Python a readable, maintainable, and widely used language that is popular with many users. Recently on Weibo, I saw Liaoche's new Python tutorial, which describes the installation and use of Python in humorous language and video, allowing beginners to quickly master py ...
With the development and popularity of artificial intelligence technology, Python has surpassed many other programming languages and has become one of the most popular and most commonly used programming languages in the field of machine learning.
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 ...
The "Editor's note" machine learning seems to have turned from obscurity to the limelight overnight, as well as more open source tools for machine learning, but the challenge now is how to get developers interested in machine learning and the data they are prepared to use to actually use them, This paper collects the common and practical open source machine learning tools in several languages, which is worth paying attention to, which is from InfoWorld. The following is the original: After decades of development as a professional discipline, machine learning seems to appear overnight as a popular business tool ...
Based on the Python Sina Weibo data reptile week China; Zhang Huian; Xiaijiang at present, many social network research is using foreign platform data, while the domestic Sina Weibo does not have a good interface to facilitate the researchers to collect data for analysis. In order to quickly obtain the data in the micro-blog, developed a support for parallel micro-bo data crawling tool. The tool can capture the user's fan information, micro-Bo Zhengwen and so on in real time, and use the keyword matching technology to match the micro-blog with the specified conditions, and to crawl the related content.
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: ...
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 ...
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