1. Just upload your python code and related input files of your Machine learning model in the Google Drive, and start running your code in Colab Notebook.
2. You can select GPU to accelerate the speed of your code to take advantage of multi-threading/processing features of GPU.
3. Store the results in Google Drive.
4. Very easy to use. Your google drive is just like a folder on your PC, and Colab Notebook is like a python interpreter. Combination of both makes your machine learning model execution on the cloud very simple.
And after the run, you can just download your results file from the Google drive.
5. Since everything runs on the server, there is no load on your PC. Your PC can be used for other tasks simultaneously.
6. If you don't have more RAM on your PC, You can easily run the computationally intensive task on Colab Notebook with GPU.
7. You can add the text in your Notebook along with the code, and share the Notebook.
1. Please add a python file editor in the Google drive so that we don't have to modify the python files locally and upload it to Google drive and then rerun on Colab Notebook. It becomes frustrating when there are frequent changes required in the code.
2. Sometimes Colab Notebook doesn't recognize the edited code file and runs on the previous version of the file. To overcome this, I need to refresh the google drive and Colab notebook every time I re-upload the edited python file to the Google Drive.
3. Can't run python code that does intensive computation on the big dataset. (Memory related error comes)
4. The execution sometimes takes a long time even with GPU.
Using it to run Machine learning code.
(Greatly benefitted by it for one of my projects. I was bound my computation power of my PC and this platform helped me a lot in running computational intensive task)