Featured post

4 Layers of AWS Architecture a Quick Answer

I have collected real interview questions on AWS key architecture components. Those are S3, EC2, SQS, and SimpleDB. AWS is one of the most popular skills in the area of Cloud computing. Many companies are recruiting software developers to work on cloud computing.

AWS Key Architecture Components AWS is the top cloud platform. The knowledge of this helpful to learn other cloud platforms. Below are the questions asked in interviews recently.
What are the components involved in AWS?Amazon S3.With this, one can retrieve the key information which is occupied in creating cloud structural design, and the amount of produced information also can be stored in this component that is the consequence of the key specified.Amazon EC2. Helpful to run a large distributed system on the Hadoop cluster. Automatic parallelization and job scheduling can be achieved by this component.Amazon SQS. This component acts as a mediator between different controllers. Also worn for cushioning requirements those are obt…

4 Top Data Mining Tools

Many data mining tools present out of those listed here top free tools useful for development.

data mining tools

4 Top Data Mining Tools

Rapid Miner (erstwhile YALE)


This is very popular since it is a ready-made, open-source, no-coding-required software, which gives advanced analytics. 


Written in Java, it incorporates multifaceted data mining functions such as data preprocessing, visualization, predictive analysis, and can be easily integrated with WEKA and R-tool to directly give models from scripts written in the former two.

WEKA


This is a JAVA based customization tool, which is free to use. It includes visualization and predictive analysis and modeling techniques, clustering, association, regression, and classification.


R-Programming Tool


This is written in C and FORTRAN and allows the data miners to write scripts just like a programming language/platform. Hence, it is used to make statistical and analytical software for data mining. It supports graphical analysis, both linear and nonlinear modeling, classification, clustering, and time-based data analysis.


Python-based Orange and NTLK


Python is very popular due to ease of use and its powerful features. There is an option available New fresh best Daily Python tips to your Inbox to learn more. 

Orange is an open-source tool that is written in Python with useful data analytics, text analysis, and machine-learning features embedded in a visual programming interface. NTLK, also composed in 


Python is a powerful language processing data mining tool, which consists of data mining, machine learning, and data scraping features that can easily be built up for customized needs.


Knime


Primarily used for data preprocessing – i.e. data extraction, transformation, and loading. This is also a part of data science and The 4 Most Asked Skills for Data Science Engineers really help to take the next step to learn more about data science. Knime is a powerful tool with GUI that shows the network of data nodes. 


Popular amongst financial data analysts, it has modular data pipelining, leveraging machine learning, and data mining concepts liberally for building business intelligence reports.

Comments

Popular posts from this blog

Hyperledger Fabric: 20 Real Interview Questions

7 Ideas to Improve Your Resume Before You Share

15 awesome Java Interview Questions to know