I recently found this funny and relatable.

I started my ML journey 6 months ago, with Harvard’s CS50 python then Andrew NG’s specialization, but until now, no one mentioned anything about, Data Structures and Algorithms. That ain’t their fault though, I avoided all that talk because I didn’t want to become a software ENG, I wanted to be an AI entrepreneur and take the lighter route. But the more I try to build stuff the more tech holes I find out in my toolkit. So ask your self what do you want to be: AI Engineer = software ENG + Data Scientist If you are working towards becoming, an ml engineer which is reportedly 80% of engineering, then go explore some real engineering stuff. For anyone starting or even in the early stages of learning I want you to check out this roadmap by codebasics :

This video is one of those "nobody should know about this except me!" videos but we are a community! https://www.youtube.com/watch?v=Al4bwR--BgY&pp=ygUmNSByZXNvdXJjZXMgZm9yIGEgbWFjaGluamUgbGVhcmluaSBqb2I%3D

This checklist can guide you through your machine learning projects. Excerpted from the 3rd edition of "Hands-On Machine Learning with Scikit-Learn,'" found in the appendix.

If you’re starting out, give your stuff away for free. When people say no, ask them why…. The reasons they list will be the hidden costs associated with your product or service.…(continue reading 👇) Please check out and engage with my LinkedIn post https://www.linkedin.com/posts/nabilyimer_why-you-should-eat-your-customers-complexity-activity-7182593995573755904-n-p0?utm_source=share&utm_medium=member_ios