My experience with Algorithms:

1. I study, fully understand topics, solve some problems.

2. Time passes, I don't really need most of this knowledge in my real world engineering.

3. I forget most of what I've learned.

I've iterated this several times, so I no longer have that motivation to (again) study algorithms without a real world need... :)

"Education is what survives when what has been learned has been forgotten." - B. F. Skinner

Not sure if Einstein had been quoted earlier than 1964 (which is the date assigned to Skinner's quote) -- but Einstein's quote is also very similar

" -- Education is what remains after one has forgotten what one has learned in school. --"

A. Einstein.

I've come to realise that trying not to understand something fully at first is a useful skill. I've often stumbled learning certain math concepts by trying to fully understand everything upfront - this is best done after having experience with using the math first.

It's useful if you're planning to interview at a place that cares about it, which includes Google, Amazon, and Microsoft. If you want to work at one of those places it's undeniably useful.

This may be a stupid question, but why is the ability to write pre-existing sorting algorithms from the top of your head necessary in those places? Don't they use standard libraries? Or is it just used as a general test of understanding of the concepts?

I think its a test for the candidates capability to grasp the concepts and coding those basic algorithms with out bugs is to demonstrate their ability for diligence.

I'd focus more on graphs and trees, and having a passing familiarity with the algorithmic and space trade offs of sort algorithms. One could argue over whether it's important philosophically, but from a practical standpoint they expect candidates to know it.

What I've been doing for the past few months is putting everything on anki flash cards. I'm sick of forgetting stuff I've learned.

Thanks for the tip! Anki looks like really useful software. Do you put asymptotic complexity of various algorithms and data structures on the flash cards or do you do more than that?

What's your advice on learning them just well enough to survive whiteboard interviews ?

I'm not interested neither in Competitive programming nor in companies who do these kind of interviews, so I can't really give you any advice here. Another advice - just skip over those places. There are tons of companies which don't do this SV-bubble whiteboard stuff.

This method of interviewing may not be perfect, but i think this is really a good way to filter the candidates out. Whats your ideal(or near to ideal) interview would be which can filter the candidates out.

It might be more or less suitable for fresh grads. But not for self-taught and especially not for mid-career professionals. The best interviews I had was concentrating on discussing previous projects and experience. Paid projects also could be a good way for some. A very simple fizzbuzz like task can be used as a first step for contacting - to eliminate CV flood.

Switch careers.

You've learned how able you were on the way.

Honestly, I don't think there are [mentally healthy] people who are "unable", rather it is "not interested [enough]".

Mapping the right algorithm to a real world need is lot more difficult as real world needs always have differences with the problems that the published algorithms solve. This is my experience. So, I end up most of the time devise my own method to solve things. When you are hard pressed for time, it is often difficult to run through books and find the right ones. The mind to read and understand complex algorithms is often overtaken by the mind to just go and solve the problem in hand in your own way.

i find these lectures difficult to watch, in the same way i found real lectures difficult to sit through

it is too raw

a 2 hour video for maybe 20 minutes of actionable content?

youtubers may be mocked for lacking credibility but at least they seek to develop a skill for editing their content

this(o) is the best source i've found on getting an understanding of the np-complete problem sphere

this in conjunction with karp's very digestible original paper(i) describing his process of reduction can help you develop a full understanding of hard problems

(o) http://mat.gsia.cmu.edu/orclass/integer/integer.html

(i) http://cgi.di.uoa.gr/~sgk/teaching/grad/handouts/karp.pdf

Good to see steve skiena on HN :). From my alma mater stony brook.

good to see a fellow seawolf

Thanks for posting this. I was about to read the entire book during the summer break, but now I would start with these videos instead.

Thank you for posting this. I am prepping for an interview at google, this is helpful.