Writing machine learning code without IDE is quite impossible. Even if we try to do so , we end up getting confused and without real time execution which could be bit problematic. To solve the same problem we have created this guide of best Python IDE for Machine Learning.
If you are not aware of what an IDE is , we’ll quickly describe once. An IDE is abbreviation of integrated development environment . It’s basically a coding platform that allows you to write, test, and debug your code in much easier way, rather than writing some individual files and then test at once. You can write and test at the same time.
We have suggested some best python ide for beginners for machine learning in the article below.
Whereas i have seen some people searching for best python ide for artificial intelligence also. i would like to suggest them that all python IDEs are almost same and offer similar functionality. So whatever we are suggesting, same can be used for artificial intelligence as well.
Simple text editors do not serve the purpose when it comes to machine learning with python. It requires importing modules and libraries, and hence a good IDE is needed.
Here is a the list of some of the good IDEs , whereas choosing best python ide for machine learning for your purpose is totally up to you.
In case you want to use a noSQL database in your project, we have prepared a guide on Best NoSQL databases , you can go through it.
One of the Stack overflow survey also shows some informational data in case you want to have a look on the same. It shows what technology alongwith IDEs that were popular among for that particular technology.
Best Python IDE for Machine Learning
1. Spyder IDE
The Scientific Python Development Environment or Spyder IDE is an open-source Integrated development environment written in Python. This IDE was released on 18th October 2009.
Spyder is one of the best IDE’s, to begin with, because it integrates the essential python libraries like ScipPy, Matplotilb, and many others.
The author of this integrated development environment is Pierre Raybaut.
Let us see some of the best features of this IDE:
2. PyCharm IDE
PyCharm is one of the most popular IDE’s in python programming whether it is used for data science or machine learning.
The beta version of this IDE was released in July 2010. The version 1.0 of this IDE was released three months later on October 2010.
Developed by Jetbrains PyCharm is a fully-featured professional IDE.
PyCharm is available in two editions:
- Professional Edition with a 30-days free trial.
- PyCharm Community Edition which is a free edition.
This IDE is also widely popular for machine learning because it provides support for various important libraries like Pandas, Numpy, Matplotlib, and many others.
Let us see some of the amazing features of this IDE:
If you work with Intellij Idea , consider looking at our guide for 20 Best Intellij Plugins That Will Make Your Life Better
3. Rodeo python
Developed by Yhat, Rodeo is an integrated development environment for python that is built expressly for data science and machine learning.
Rodeo IDE helps to interact and explore with plots and data. The Rodeo IDE has many similar features like Sypder.
This IDE uses the IPython Kernel.
Some of the Key features of Rodeo are:
4. Jupyter Notebook
Born out of IPython in the year 2014 Jupyter Notebook is a combination of an IDE and a server to run your projects.
This project was started to support data science and scientific computing across most of the programming languages.
The term Jupyter stands for Julia, Python and R. However, this does not mean that Jupyter is confined to only these three programming languages.
Jupyter Notebook is a web-application based on the client-server structure. This allows you to manipulate, analyze and create documents in the form of notebooks.
Apart from working as an IDE, Jupyter Notebook can also be used to write blogs or use it as an education tool.
Let us see some other features of Jupyter Notebook:
Officially released on 25th October 2019 Geany is a light-weight Python IDE for machine learning. Written in C and C++ the IDE is authored by Enrico Troger. Despite being a small IDE, Geany is capable of doing most of the tasks that other IDE’s can do.
Some of the features of Geany IDE are:
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So far we have discussed various IDE’s that you can use for machine learning. These IDE’s are not only capable to start with machine learning but can also be used for other purposes like Data Science. Since chosing best python ide for machine learning depends totally with respect to the nature of your product. All of these IDE’s have their own features so, you can choose the most suitable IDE for your project.