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I understand both are built over Jupyter noteboooks but run in cloud. Why do we have two then?
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Google Cloud DataLab is a tool for exploratory data analysis, data visualization, and building machine learning models. It is a powerful BI Engine tool for structured and unstructured data to analyse the patterns in every dataset.
Google Colab is a free cloud service that offers Jupyter Notebooks via remote servers. Students can use GPU and TPU resources from Google to run their Python code using Google Colab.
Google Colab's major differentiator from Jupyter Notebook is that it is cloud-based and Jupyter is not. This means that if you work in Google Collab, you do not have to worry about downloading and installing anything to your hardware.
Jupyter is the only thing these two services have in common.
Colaboratory is a tool for education and research. It doesn’t require any setup or other Google products to be used (although notebooks are stored in Google Drive). It’s intended primarily for interactive use and long-running background computations may be stopped. It currently only supports Python.
Cloud Datalab allows you to analyse data using Google Cloud resources. You can take full advantage of scalable services such as BigQuery and Machine Learning Engine to analyse, manipulate and visualise data. You can use it with Python, SQL, and JavaScript.
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Google Colaboratory is free. But, you are limited to one spec of cpu/ram/disk/gpu.
Google Datalab is paid. You pay for whatever specs you want.
The notebook interface is also a bit different between the two.
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