stylegan2-projecting-images VS Spyder

A Colab notebook.

To play with the dataset, we first must create a Jupyter notebook, a powerful and popular tool among data engineers. I created mine on Google Colab.

Please head over to the Google Colab

But regardless of what you want to do, you'll probably use Python. In this context, a good way to work with Python is using Jupyter Notebooks. So you should start with installing Python and Jupyter and go from there. If you want to get started without installing anything, Google Colab gives you a remote Jupyter Notebook which runs in the browser for free.

访问 Google Colab 。

Remember school days when you'd share notes with classmates? Jupyter takes that spirit and amplifies it. Once you've crafted your Notebook, you can share it with peers, collaborators, and the world. Platforms like GitHub and Google's Colab natively render Jupyter Notebooks. It's like penning an open letter to the world but in a delightful mix of code, text, and visuals.

Open your web browser and navigate to Google Colab.

Using Google Colab you can develop Python codes, similar to Jupyter Notebooks. You will have an environment prepared with various Python libraries. In addition you have tips on small codes for development, some tutorials, gihub connection, cloud -saved notebooks and more.

IDE-wise, I find Spyder to be the most R-like. If you are comfortable with R Studio, maybe check it out.

For anyone else who hadn’t heard of Spyder: https://www.spyder-ide.org/

Spyder

Spyder - a popular editor for scientific work, the default option if you get the Anaconda implementation of Python which includes many packages used in science and engineering fields

I also have a fondness for Spyder, which was my first non-IDLE IDE experience. It is heavily geared toward scientific computing.