I just want to know what is the best way to study well for this course and the ungraded labs ??? And should i implement the same code of the Algorithm from Scratch as it is at Optional labs. if yes, so how ?? Or we will only implement the algorithms by real-world tools and libraries like sklearn and so on ?
i just watch the lectures (Week 1 & 2) and study the theoretical part from the slides
Hi @youssef26 ,
Optional labs are designed to help you familiar with certain aspects of the subject. Each graded lab has its own goal and objective. You need to follow the instruction carefully when attempting the exercises.
Hello @youssef26,
These labs cover the concepts discussed in the lectures. If you have no problem understanding them, that’s good. If you can also explain them in your own words, that’s better. If you can even code them out from scratch, that’s the best.
I think it is sufficient to achieve the “good” part for you to move on, and I would encourage you to attempt the “better” part to consolidate your knowledge. However, the “best” part can really be left to the future when it is needed in your own projects. Perhaps it will never be needed because you have good alternatives like Sklearn; if so, just let it be.
I think a good strategy is to just follow the path set out in these courses and not worry about missing out on anything. After that, find yourself a simple machine learning project and you can gain practical experience from there, during which you may revisit the materials as you need (make sure you save your own copy of the labs).
Cheers,
Raymond