Python Data Analysis Course

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Python Language Machine Learning Library Top 10

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.

Using Python to build a mapreduce log analysis platform based on Hadoop

Large flow of log if the direct write Hadoop to Namenode load, so the merge before storage, you can each node log together into a file to write HDFs.  It is synthesized on a regular basis and written to the HDFs. Let's look at the size of the log, 200G DNS log files, I compress to 18G, if you can use Awk Perl, of course, but the processing speed is certainly not distributed as the force. Hadoop Streaming principle Mapper and reducer ...

Recommended! The machine learning resources compiled by foreign programmers

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 ...

10 program languages to help you read the "Secrets" of Big Data

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 ...

Nine programming languages needed for large data processing

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: ...

Nine programming languages needed for large data processing

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: ...

12 big killer of Big data analysis

As data grows in hundreds of terabytes, we need a unique technology to address this unprecedented challenge. Big data analysis ushered in the great era of the global organizations of all walks of life have realized that the most accurate business decisions from the facts, not a figment of the imagination. This means that they need to use the decision model and technical support based on data analysis in addition to the historical information of the internal trading system. Internet-clicked data, sensing data, log files, mobile data with rich geospatial information and various kinds of comments involving the network have become various forms of mass information. ...

12 big killer of Big data analysis

As data grows in hundreds of terabytes, we need a unique technology to address this unprecedented challenge. Big data analysis ushered in the great era of the global organizations of all walks of life have realized that the most accurate business decisions from the facts, not a figment of the imagination. This means that they need to use the decision model and technical support based on data analysis in addition to the historical information of the internal trading system. Internet-clicked data, sensing data, log files, mobile data with rich geospatial information and various kinds of comments involving the network have become various forms of mass information. Have a great ...

Top 10 data mining tools most needed for big data

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.

Data import HBase Three most commonly used methods and practice analysis

To use Hadoop, data consolidation is critical and hbase is widely used. In general, you need to transfer data from existing types of databases or data files to HBase for different scenario patterns. The common approach is to use the Put method in the HBase API, to use the HBase Bulk Load tool, and to use a custom mapreduce job. The book "HBase Administration Cookbook" has a detailed description of these three ways, by Imp ...

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