Being coding-focused, the course does recommend knowing programming basics. No prior machine learning experience is required.
Since September I have been taking the famous Stanford Machine Learning course by Prof. Andrew Ng on Coursera. I must admit that this certainly helps me with the zero-to-GANs course.
It is indeed a wonderful time to learn ML, given the large selection of online courses and code camps. Everyone has their own preferred style of learning. I can say that not everyone will like the pace and style every course. This one is no exception. But I think with a little bit of patience anyone can get accustomed to this course due to its simplicity behind all of the jargons. I am extremely grateful for Jovian and its team to provide this course free of cost. (No, I am not paid, nor do I receive any benefit from Jovian.ai for writing this!)
I was skeptical if I will be able to follow the course. With 2 lessons and assignments complete, I think I will survive through this. I managed to survive 2020 after all, what’s in another course!
With that intro out of the way… (I promise, future stories will get straight to the point, unlike recipe articles)
The 1st assignment of this course is aimed to get used to PyTorch functions, Google Colab, Jovian Jupyter Notebooks. On that note, here are 5 PyTorch functions from several of them that I tried. And I hope they will get you hooked up to practice PyTorch.