Python Statistics

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 ...

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.

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 ...

COLLECTD is a small, modular daemon for regular statistical collection of system information and for storing valuable information in a variety of ways. The main features include: a large number of plug-ins to collect CPU, disk and memory utilization, network interface and DNS communication, network latency, database statistics, and so on. Custom statistics can be easily added in a variety of ways, including executing any programs and plug-ins written in Perl. Its advanced features include a powerful network code to collect statistics for the entire setup, as well as SNMP Integrated query network devices. Col ...

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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In machine learning applications, privacy should be considered an ally, not an enemy. With the improvement of technology. Differential privacy is likely to be an effective regularization tool that produces a better behavioral model. For machine learning researchers, even if they don't understand the knowledge of privacy protection, they can protect the training data in machine learning through the PATE framework.

Author: Chszs, reprint should be indicated. Blog homepage: Http://blog.csdn.net/chszs Someone asked me, "How much experience do you have in big data and Hadoop?" 　　I told them I've been using Hadoop, but I'm dealing with a dataset that's rarely larger than a few terabytes. They asked me, "Can you use Hadoop to do simple grouping and statistics?" 　　I said yes, I just told them I need to see some examples of file formats. They handed me a 600MB data ...