Google Colab: the power of the cloud for machine learning – DataScientest

Hosting in the cloud

A key feature of Google Colab is that it is hosted in the cloud. This means that there is no need to install Python or other libraries on your computer. Everything happens directly in a web browser. All you have to do is sign in to your Google Account and youre ready to go.

Pre-installation of numerous libraries

Google Colab comes with many Python libraries pre-installed. This includes libraries commonly used for data science such as NumPy, Pandas, Scikit-learn, TensorFlow and PyTorch, as well as visualisation libraries such as Matplotlib, Seaborn and Plotly, making it easy to create graphs, charts and visualisations to explore and present data. You dont need to worry about installing these libraries, which greatly simplifies the configuration of your environment.

Google Colab allows you to run system commands directly from a notebook. So if you need specific libraries that arent pre-installed, you can install them directly from a notebook using the pip command. This allows you to extend the functionality of your environment.

Access to computing resources

Google Colab offers free access to graphics processing units (GPUs) and tensor processing units (TPUs), which are extremely useful for computationally intensive tasks such as deep learning models. You can activate these hardware accelerations with just a few clicks. This speeds up the model training process, reducing the time needed to obtain results.

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Google Colab: the power of the cloud for machine learning - DataScientest

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