Google’s Colaboratory (Colab) is a Jupyter-based research tool for machine learning education and research. The Colab Jupyter notebook environment is a standard virtual machine that requires no setup to provision and to use.
The Colab environment’s virtual machine has access to 12 GB of RAM, which is sufficient to practice many machine learning problems. The intended use for the virtual machine is interactive modeling and learning. The virtual machine can terminate after some time, and we will need to reconnect to another Colab virtual machine. Another word, the Colab environment is not suitable for long-running machine learning jobs, but the Colab virtual machine does include access to a GPU.
As I work on practicing and solving machine learning (ML) problems, I find myself repeating a set of steps and activities repeatedly. Thanks to Dr. Jason Brownlee’s suggestions on creating a machine learning template, I have pulled together a set of project templates that can be used to support regression and classification ML problems using Python in Colab.
You will find the Python templates (including the ones for Colab) from the Machine Learning Project Templates page.