Best 2021 Resources for Learning about AI/ML

Wed, 20 Jan 2021 19:10:59 +0000

For upskilling on AI/ML, I prefer taking a top-down approach i.e. starting with high level concepts then proceeding to more foundational topics (read: delve more into the theory) . I liked taking the breadth-first approach (rather than a depth-first approach) to initially understand AI/ML. Once I had a solid foundation, I easily pivoted to learning a specific topic, like masked regional CNNs, for building expertise through real-world experience.

I took multiple courses and read several authors at the same time. You want to find the right sources of information for you and there are so many options out there, so explore. Sometimes I need to read or watch something a few times from different folks before it just clicks. This ultimately accelerated my learning of concepts. Completion of courses should not be the ultimate goal as some courses cover trivial topics and others go too deep into other topics.

Fastai’s Practical Deep Learning for Coders Course Release - 2020 Update!

Thu, 03 Sep 2020 17:48:01 +0000

On Aug 21st, 2020, fastai released a new version of their Practical Deep Learning for Coders -Part 1 course. This course is a must-take for new and intermediate deep learning practitioners. It is well done and teaches you intuition without drowning you in theory. The only prerequisites are some high-school math, and a year of coding experience (preferably in Python). This course is free and can be done without any installation, by taking advantage of the Colab and/or Gradient platforms, which provide free, GPU-powered Python notebooks. Go here to learn more about the course.

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Best 2021 Resources for Learning about AI/ML

Fastai’s Practical Deep Learning for Coders Course Release - 2020 Update!