interactive data visualization tools

a cross-cutting area influenced by many disciplines, including database system, statistics, machine learning, visualization and information science, etc. data mining repeatedly using multiple data mining algorithms to determine patterns or reasonable models from observational data is a decision support process. By pre

1, RapidMiner The tool is written in the Java language and provides advanced analysis techniques through a template-based framework. The biggest benefit of this tool is that users don't have to write any code. It is provided as a service rather than as a local software. It is worth mentioning that the tool topped the list of data mining tools.In addition to data mining, RapidMiner provides features su

numpy arrays and array-oriented computations. 3. Matplotlib Matplotlib is a powerful data visualization tool and drawing library, is mainly used for plotting data diagram of the Python library, provides a variety of visual graphics to draw the command font, simple interface, you can easily grasp the format of the graphics, drawing all kinds of visual graphics. M

3. Large data processing capability (1) Perfect fusion with ODPs, release its processing ability (2) Support the operation and management of a single enterprise level 100,000 task (3) Analysis tool supports the real time OLAP analysis of billion-level data 2. Product function DPC provides full link data tool solutions for all, and everyone can find

Original Author: Chandan Goopta. [Chandan Goopta is a data research expert from the University of Kathmandu (Nepal Capital) dedicated to building intelligent algorithms for affective analysis. ] original link:http://thenewstack.io/six-of-the-best-open-source-data-mining-tools/ In this day and age, it is no exaggeration to say that

, extensible, and optimized for query performance.9. The most active project in Spark--apache Software Foundation is an open source cluster computing framework.Spark is an open-source cluster computing environment similar to Hadoop, but there are some differences between the two that make spark more advantageous in some workloads, in other words, Spark enables the memory distribution dataset, in addition to providing interactive queries, It can also o

hive-supports class-SQL encapsulation in Hadoop, which turns SQL statements into Mr Programs to execute. The Apache kafka– high-throughput, distributed, messaging-subscription system was first developed by Linkin. Akka–java was developed to build highly concurrent, JVM-based resilient message-driven applications. hbase-The open source distributed non-relational database developed by Google's bigtable paper. The development language is Java, with HDFs as the underlying storage. neo4j

Original name: 7 tools to fire up Spark ' s Big Data EngineSpark is rolling a storm in the field of data processing. Let's take a look at some of the key tools that have helped Spark's big data platform through this article.Spark Eco-system sentient beingsApache Spark not on

R Tokenize Nltk.tokenize (UK), Jieba.tokenize (middle) Tau::tokenize Stem Nltk.stem Rtexttools::wordstem, Snowballc::wordstem Stopwords Stop_words.get_stop_words Tm::stopwords, Qdap::stopwords Chinese participle Jieba.cut, Smallseg, Yaha, finalseg, genius Jiebar TFIDF Gensim.models.TfidfModel Unknown Topic model category Python

Spark is rolling a storm in the field of data processing. Let's take a look at some of the key tools that have helped Spark's big data platform through this article.Spark Eco-system sentient beingsApache Spark not only makes big data processing faster, but also makes big data