Deep Learning with PyTorch: zero to GANs course. First assignment.

Original article was published on Deep Learning on Medium

Deep Learning with PyTorch: zero to GANs course. First assignment.

Recently I discovered a very interesting course on the freeCodeCamp.org Youtube channel that was provided for free called Deep Learning with PyTorch: from ‘zero’ to GANs. I was immediately hooked. This website is a good one to learn software skills from a basic level to intermediate or even close to advanced level.

The course is well organized and presented me to a good project named Jovian.ml. This is a nice platform for Machine Learning/Data Science course learning and it allows for a web browser Jupyter Notebooks editing environments experience. We can run Notebooks, fork existing ones, save and download our work to later share with wider audiences or anyone intersted or requiring these types of development. This is also a good way for software freelancers gig workers to test and share their work before full deployment.

With this post I would like to share my first Notebook I built at the Jovian platform. It is the first assignment of the course and I have a notebook detailing 5 functions we can do with the PyTorch torch.Tensor function API.

I will share the complete Notebook. In later posts I might get into the details of every Input/Output Notebook cell. But in this first assignment I think the whole Notebook is basically self-explanatory and easily understandable and not requesting much in a very detailed explanation. Some topics assumes knowledge of some higher education mathematics and the basics of Machine Learning/Data Science.

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