Introduction to Google Colab
The adventages of using this services are:
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No need to configure environment for your project
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It has access to Google’s hardware. With the cloud computing technology it is possible for you to execute your code using hardware from the providers. A lot of people using this service to train their Deep Learning projects because it needs a lot of GPU’s power.
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It has access to share your notebook with the others, so like its name, you can colaboratory with other people to work on your project.
Oke, so let’s try to open their site with this link https://colab.research.google.com
Terdapat pilihan untuk mengakses notebook yang telah dibuat sebelumnya maupun untuk membuat notebook baru. Misal kita akan membuat notebook baru maka klik new notebook. Setelah itu klik tombol connect pada sebelah kanan atas sampai terdapat status connected lalu akan muncul indikator RAM dan ukuran disk yang tersisa.
There are options to access notebook you’ve been created before or creating a new one. For the example we want to create new notebook, so click new notebook and then click Connect button on upper right until the status shown connected and we can see the indicator of RAM and disk availability
Google Colab provides options to access cloud file using Google Drive on left panel. Click on folder icon and you need to authenticate your account. This is very good feature if you have a lot of data you can upload to your drive first and import it to your Colab session. Google Colab service lasts only for 12 hours in one session. To change the runtime type using GPU or not you can change with Runtime > Change Runtime Type then select GPU as hardware accelerator.
Try to insert command with +code button or with Ctrl+M B shortcut. Insert your command on code box. Like on this example you are trying to know your current directory. Colab is using Linux OS for their service, so some Linux command is accessible. To run your command click run button or press Ctrl+Enter
Thank you! :)