Top 4 Python IDEs For Machine Learning & Deep Learning
This article talks about introducing 4 Top Python integrated development environments for beginners.
You know Python is very useful and easy to develop a program quickly. Many young people are learning the programming language to become data scientists and developers. If you are a Python beginner, you will be confused to choose an IDE (integrated development environment) for the first time. Many development environments are convenient, sometimes they are inconvenient. Let’s talk about Top 4 Python IDEs.
1. Google Colab
I am sure you know Google Colab. It is short for Google's Colaboratory services. Google Colab is provided by Google Support and is a free Jupyter Notebook development environment based on Google Cloud. You can use Python and run it in the browser. Also, you can work on your tasks through your tablet PC. If your computer does not have a GPU or has low specs, I recommend you to use it.
Pros
- It doesn’t have to download Tensorflow, Keras, and Pandas.
- This is a good virtual IDE for students to study data science and AI.
- You can easily upload your projects on GitHub.
- Colab is useful for machine learning and deep learning.
- You don’t have to install any libraries.
Cons
- It takes time to upload a file (If CSV is big ).
- It is necessary to adjust the version with the tensor flow you worked on.
- Internet should be connected.
2. Repl.it
While I was looking for the best way to use Python with a Galaxy tab, I found the Python IDE “Repl.it” which was found on a foreign developer’s YouTube channel. It provided 50 languages such as Java, C++, and various programming languages. The good thing is that you can run any language in Repl.it.
Pros
- It can be easily used on a tablet computer.
- Users are able to practice any programming language.
- Running and hosting services are available.
- GitHub is linked.
Cons
- Internet should be connected.
- Execution is a bit slow.
- Sometimes, the library cannot be downloaded.
- Scikit-learn, Tensorflow, and Pandas libraries must be downloaded from new files all the time.
3. Jupyter Notebook
Jupyter Notebook is an environment that allows users to run the Python interpreter on a web browser. In addition, it is an effective environment for writing code and documents as a single file. I often use it for working on a machine learning project.
Pros
- It is easy to use to analyze data.
- Users can easily check the code they wrote.
- It is a good IDE after Google Colab.
- It works on the iPad and Galaxy Tab.
Cons
- The installation of the Jupyter Notebook is a little complicated. The best way is to install it on Anaconda.
- It must connect to the host.
- GitHub is not linked.
- Tensorflow can be downloaded separately.
- IDE should be installed.
4. PyCharm
Finally, PyCharm is the integrated development environment that helps users to develop a program easily. It is closer to development than data analysis because it is useful to develop a GUI (game or utility). You can use Jupyter Notebook or Colab to create a visual project, but this development environment is for creating a platform. If you want to become a developer, then you should use the Python IDE.
Pros
- It is very helpful to develop a GUI.
- It is enough to use the community version for free.
- Web development is also possible with PyCharm.
- Users can download a package easily.
- It is convenient to manage Python files and ternary management.
Cons
- PyCharm is not available for a tablet PC.
- It should be installed.
- The professional version is somewhat expensive.
- The community version is idle for python development only and does not allow to use of other programming languages.
- It can be complicated for beginners to set a virtual environment variable.
Epilogue
Among integrated development environments, Google Colab and Jupyter Notebook are useful for me to analyze data and develop a GUI. Also, they are not complicated for me to check a scripting language.
What is your favorite Python IDE? If you wanna share your favorite IDE or follow me, please click those two links below. I look forward to receiving your favorable response.
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