Top 10 Tools that are shaping the Future of Data Scientists

Here are the top Data Science tools that are used by most of the data scientists. Have a look at them –

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Python is a popular programming language that offers a large number of libraries for data science operations. Some of them are numpy, matplotlib, tensorflow, opencv etc.

R is a library that is mostly used for statistical modeling. It also offers variety of visualization and analytical tools. Ggplot2, dplyr, mlr, lubridate are some of the important libraries of R. To explore more in R you should check a complete R tutorial series.

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SAS is a closed source proprietary software that is used for a number of data operations including analysis and machine learning. It is stable and is trusted by industry professionals around the world. Learn about SAS in detail.

 

SQL is the bread and butter of all the data science operations. It is used for extracting information from the databases. It is the time to master SQL for FREE.

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Weka is an open source data mining software that provides GUI support for performing various machine learning operations on the data model.

Hadoop is a big data tool that is used for processing large amount of data. It is a highly scalable platform that can accommodate large scale computations. Hadoop is very important for data scientist. If you have this skill it will add a good value in your resume and helps you get a better job.

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Spark is an open-source, fast and efficient data processing engine that comes with revealing development APIs. What makes Spark special is its data streaming capability.

 

D3.js is a javascript library that allows you to make interactive visualizations on your web-browser. With its APIs, you can use several functions to create dynamic visualization and analysis of data in your browser.

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Tableau allows you to make interactive visualizations. It offers Desktop as well as cloud solutions for your business requirements.

 

TensorFlow is an advanced machine learning library that provides support on Python and C++. With this, you can build powerful deep learning models.

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These are some of the important tools that are used by every data scientist. Also, to learn each tool, I have provided you the links. Start learning these tools, upgrade your skills, and step up in data science field. Also, you can check the latest article on how can you get your first job in data science. Don’t forget to add your feedback in the comments below.

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