- Google Colab Tutorial
- Google Colab - Home
- Google Colab - Introduction
- What is Google Colab?
- Your First Colab Notebook
- Documenting Your Code
- Google Colab - Saving Your Work
- Google Colab - Sharing Notebook
- Invoking System Commands
- Executing External Python Files
- Google Colab - Graphical Outputs
- Google Colab - Code Editing Help
- Google Colab - Magics
- Google Colab - Adding Forms
- Google Colab - Installing ML Libraries
- Google Colab - Using Free GPU
- Google Colab - Conclusion
- Google Colab Useful Resources
- Google Colab - Quick Guide
- Google Colab - Useful Resources
- Google Colab - Discussion
Google Colab - Introduction
Google is quite aggressive in AI research. Over many years, Google developed AI framework called TensorFlow and a development tool called Colaboratory. Today TensorFlow is open-sourced and since 2017, Google made Colaboratory free for public use. Colaboratory is now known as Google Colab or simply Colab.
Another attractive feature that Google offers to the developers is the use of GPU. Colab supports GPU and it is totally free. The reasons for making it free for public could be to make its software a standard in the academics for teaching machine learning and data science. It may also have a long term perspective of building a customer base for Google Cloud APIs which are sold per-use basis.
Irrespective of the reasons, the introduction of Colab has eased the learning and development of machine learning applications.
So, let us get started with Colab.
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