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Anaconda: The first choice for beginner Python, entry machine learning

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.

SQLObject v1.1 publishes the Python database object mapping framework

SQLObject 1.1.0 release, SQLObject is a popular Python database object mapping framework, the mapping rule is table-> class, Field-> properties. The Object Relational Mapping tool helps increase productivity by providing classes and objects to manipulate database tables. Python's Best object-relational mapping tool is sqlobject--an open source project that almost completes all the operations required by the programming database. This article introduces SQLObject and its functions. After reading this article ...

SQLObject 1.1.3 Publish Python database object Relational mappings

Sqlobject is a Python database object relational mapping. For example, a library will wrap your database table in a Python class. Currently supports MySQL through the MYSQLDB package, supported by the PSYCOPG package postgresql,sqlite,firebird,maxdb (SAP DB), MS SQL and Sybase. Also supports the Python 2.4 version. SQLObject version 1.1.3 Fixes Http://www.aliyun.c ...

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: ...

Don't get into the same old Hadoop, your data isn't big enough.

This article, formerly known as "Don t use Hadoop when your data isn ' t", came from Chris Stucchio, a researcher with years of experience, and a postdoctoral fellow at the Crown Institute of New York University, who worked as a high-frequency trading platform, and as CTO of a start-up company, More accustomed to call themselves a statistical scholar.     By the right, he is now starting his own business, providing data analysis, recommended optimization consulting services, his mail is: stucchio@gmail.com. "You ...

Why do some companies prefer to use the R + Hadoop solution in the machine learning business?

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 ...

When to use Hadoop

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 ...

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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