In this post, we are going to learn Setup the development environment for Tensorflow, you might be expecting to download and install a lot of packages on your particular operating system, set up IDEs, code editors, and Jupyter notebook.
But hold on, my honest feedback regarding this is that, this is a hurdle for new learners, we should focus on learning the framework instead of learning the environment setup at early stages, that’s why I decided to make this thing simplest, but before that, I want to mention that, this is my personal experience and point of view you may differ with me.
There's a great tool built by Google named Colab, which allows anybody to write and execute arbitrary python code through the browser, and is especially well suited to:
- Machine learning
- Data analysis
Colab is a hosted Jupyter notebook service that requires no setup to use while providing free access to computing resources including GPUs.
So, We need only two things for this setup:
- Gmail account
Open your browser and log onto colab.research.google.com, then hit the singin button and log in with your Gmail account.
- Now, to create a new notebook click file and a new notebook
- A notebook is composed of cells, each of which can contain code, text, images, and more.
- Colab connects your notebook to a cloud-based runtime, meaning you can execute python code without any required setup on your own machine.
That's it for now, we will set up the development on our systems in this post click here, but now we should focus on learning instead of the development setup.
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