Top 8 IDEs for Machine Learning and Data Science (Part 2)

In the previous article we have talked about some IDEs for R and Python. In part 2, we will introduce some IDEs for other programming languages.

OS: macOS, Windows, Linux

Spyder is a scientific environment designed for use by scientists, engineers, and data analysts. It is a comprehensive development tool, which has so many functionalities like editing, analysis, debugging, and profiling. Moreover, those options such as data exploration, interactive execution, deep inspection, and superb visualization are what it’s capable of. You can also extend its abilities via plugins and API.

Spyder has a multi-language editor with a class browser, code analysis tools, automatic code completion, go-to definition, and horizontal and vertical splitting. The other advantages about using Spyder is the great community support you can get along with entire complete documentation.

OS: macOS, Windows, Linux

Scala IDE for Eclipse would be one example of IDE uses machine learning production codes. It provides complex editing and debugging support for the building of Scala and Scala-Java based applications. It also allows references from Scala to Java and vice versa.

Like any modern IDE, it has code completion, semantic code highlight abilities, and go-to definition. It also catches compilation errors as you type.

OS: macOS, Windows, Linux

IntelliJ IDEA is another IDE from JetBrains. It is famous for ergonomics and the intelligent coding assistance it provides for developers using Java, JavaScript, and other languages. The Scala plugin expands IntelliJ IDEA’s toolkit with support for SBT, Scala, Scala.js, Hocon, and Play Framework.

It has functionalities of coding assistance, navigation, search, information about various types, and also integration with SBT and other build tools.

OS: macOS, Windows, Linux

Geany is one of the best IDEs for data science with Python. The IDE was created by Enrico Troger and officially released on October 19, 2005.

It has been written in C & C++ and designed primarily a Python machine learning but has support for over 50 program languagues now.

Another advantage of Geany is that it is lightweight but still so powerful. One more thing about Geany’s editor, it supports highlighting of the Syntax and line numbering for your projects.

OS: macOS, Windows, Linux

Of all the IDEs for data science and machine learning, Rodeo is one of the most versatile. It uses IPython kernel and was authored by Yhat. It is known for its ability to let users explore, compare, and interact with data frames and plots.

Above are some of the most popular IDEs for Python, Scala, R programming languages. There are still many more worth mentioning like Jupiter Notebooks, Juno, Atom, Sublime Text 3, and the Julia extension for Visual Studio Code. If you are interested in data science, you can investigate those IDEs. Although it’s not really suitable for your workflow, it’s better to stay up to date and equip as much as knowledge possible.

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We support all AI IDEs & Libraries such as: TensorFlow, Jupyter, Anaconda, Python, MXNet, PyTorch, Keras, CNTK, Caffe and so on.

This is our packages tailored for AI/ Deep Learning:

Plus, at iRender, we provide you more support than just those config.

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Thank you & Happy Training!

Source: medium.com

*Note: all images are from medium.com