Starting with Machine Learning on devices like MCU - Part 11 (Tools for coding models as we have IDE for MCU)

When we write a program for MCU, we know that we have IDE like KEIL, Simplicity Studio, Code Composer Studio, Arduino, Eclipse, VS Code and then the code compiles with the compiler inbuilt/configured in these IDE. Similarly, for writing code for Machine Learning, we use Jupyter notebooks or Jupyter Lab. Specifically for writing and running code, usually Python.

To use Jupyter notebook, we can use Anaconda distribution or online Google Colab (Google Colaboratory). 

Anaconda is open-source software (commercial edition also exist). You need to install the distribution on your system. It includes open-source tools like:

• Python
• Conda (the package and environment manager)
• Jupyter Notebook
• NumPy, Pandas, Matplotlib, etc.,

Google Colab is a free online platform provided by Google that lets you write and run Python code in your web browser. No installation needed.

• It’s like an online Jupyter Notebook, hosted on Google’s cloud servers.
• You can write code, add text, run experiments, and visualize results, all in one notebook-style interface.
• Runs Python code directly in the browser.
• Integration with Google Drive, meant you can save notebooks to your Drive or share them easily.