How to Use Mojo Programming Language?

To use Mojo and access the Mojo Playground, follow these steps:

Sign up: Sign up for access to the Mojo Playground. Visit the Mojo Playground website and sign up for access. Fill out the necessary form with your details, including your email address.
Wait for access: After signing up, you'll need to wait for the Mojo Playground team to grant you access. They will review your request and provide you with login credentials.
Log in: Once you receive access, https://playground.modular.com/hub/login go to the Mojo Playground website and log in using the email address you provided during sign-up. Use the provided login credentials to access your account.
Explore the Mojo Playground: Inside the Mojo Playground, you'll find a JupyterHub environment where you can work with Mojo. Every user has access to the same Mojo standard library, but you also have a private volume where you can write and save your own Mojo programs.
Check out the example notebooks: The Mojo Playground includes several example notebooks to help you get started. The "Hello, Mojo" notebook is a good starting point, as it provides a walkthrough of the major language features. You can also explore other example notebooks to learn more about Mojo's capabilities.
Participate in the Mojo community: Engage with other Mojo users in the Mojo community. You can share feedback, ideas, or issues you encounter while using Mojo. Additionally, you can chat with other users and exchange Mojo code for collaboration and learning.
Report issues and provide feedback: If you encounter any bugs or have suggestions for improvement, make sure to report them. You can submit issues and provide feedback on the Mojo Playground's GitHub page. This helps the development team address problems and enhance the overall Mojo experience.

Remember, as the Mojo Playground is a cloud-based environment, the number of vCPU cores available may vary. Therefore, baseline performance may not accurately represent Mojo's capabilities. However, you can refer to the Matmul.ipynb notebook to see Mojo's relative performance compared to Python.