Google Colab: A Promising Platform

With drift of world from low complexity to high complexity problems. Scenario in data science solutions also becoming more polished. Drift happening from Machine learning solutions to Deep learning solutions.

From budding data scientists to researchers, everyone is moving towards deep learning for most of their AI related solution. Reason behind, scope of AI solutions becoming wider and hence the number of input features becoming more. Rather than feature selection through domain expertise and given the scenario mammoth dataset, deep learning becoming apt and hence more eminent. Everyone is looking forward for good infrastructure, which can run computation of deep learning, really fast.

Here comes Google Colab, which can do wonder for you, without any cost associated.

Google Colab provides cloud service through Ipython notebook, where mammoth datasets can be fetched from Google drive or Github. One need not to worry about the limited hardware of their local system. In-fact, the notebooks created here on colab, can also be saved to Google drive, in hassle-free manner. Its just all your sessions, will be required go through one authentication step.

The forte of Google Colab is that, it provides free GPU and TPU for excessive computation-oriented task such as Deep learning projects.

One can investigate the devices available:

Type in ipynb file:

Go to “Runtime” to run it.

Output:

This should show all your CPU’s, GPU’s and TPU’s. Then one can opt for, whichever device one needs to use.

I feel this is the right platform for your project POC’s, Kaggle competitions and experimentation's.

Happy Learning!