Build Your Own Deep Learning Library, From Scratch

Have you ever wondered how deep learning libraries like PyTorch and Tensorflow actually work? If you're like me, this question has probably been tugging at you for a while, and there isn't really any material online that teaches you about these libraries' internals, outside of some obscure research papers and short of diving directly into the code. Late last year, I had finally had enough of wondering, and I embarked on a quest to dispel the mystery of these deep learning frameworks once and for all. I learned how they actually work, and I distilled all of the knowledge I gained into my new course at In this course, you'll learn about advanced deep learning concepts like automatic differentation, hardware level optimizations, regularization techniques, Maximum a Posteriori, and so much more. And you'll do all of this by building your very own deep learning library, COMPLETELY FROM SCRATCH! It's the first course of its kind, and one that will prepare you exceedingly well for a career as a data scientist or machine learning engineer. It's truly a one of a kind course and learning experience.

What's more, I plan to continue researching advanced deep learning tools and topics that haven't been covered in other online courses and create courses based on their implementation. If you sign up for the site now, you'll gain access to all these new courses as I develop them, all for one low, monthly price. It's an unbeatable offer that you won't find anywhere else.

As a thank you for reading my blog, I'm going to give 25% off a Flamethrower AI membership in perpetuity to the first 30 people who email me at with the subject line "Flamethrower AI Blog Discount". I truly hope you're as excited for this course as I am, and I look forward to teaching you all about the advanced deep learning concepts you never knew about.

All the best,