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Algorithms

khanacademy.org

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Re: Algorithms

#111

Post by imakecomments »

b3b0p wrote: post #103

The Coursera Stanford [0] and Princeton [1] courses start again soon, February 20 to be exact. Not sure which one is better, but to refresh my atrophied CS skills of 10 years I've joined the Stanford course. Not sure how it compares to the Khan Algorithms course. Anyone have any feedback? [0] https://www.coursera.org/learn/algorithm-design-analysis/ [1] https://www.coursera.org/learn/algorithms-part1/

This is just my opinion and I'm sure it differs from others...

Roughgarden's class is advance and expects mathematical maturity. You may find his course quite fast and rough if you are a beginner.

Sedgwick's class is much easier. He is a bit boring and tries to use "real life" examples (in some instances) from the physical sciences to make the material relatable. This in my opinion detracts from the material. Also, he doesn't always fully explain where he got some of the big ohs here and there.

My advice? Follow MIT's OCW course (it uses CLRS). Supplement it with Algorithms Unlocked, the Khan Academy link in OP and CLRS. If you use those 4 resources and put in the work you'll understand the material.

All 4 sources have Thomas C's DNA touch to it (he is the C in CLRS). So you'll find it consistent when you read from one source to the other. After reading/hearing the same thing about 4 different times in 4 different ways it'll begin to click.

Order of easiness is probably Khan Academy > Algorithms Unlocked > MIT Algorithms Course > CLRS.

Algorithms Unlocked is like "pre-CLRS" and Khan Academy's version is the TL;DR version of Algorithms Unlocked.

Hope this helps.

Below are the links,

https://www.amazon.com/Algorithms-Unlocked-Press-Thomas-Corm...

https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press...

https://www.khanacademy.org/computing/computer-science/algor...

https://ocw.mit.edu/courses/electrical-engineering-and-compu...

Re: Algorithms

#112

Post by RandomOpinion »

gech wrote: post #44
tomwphillips wrote: post #23

This is an excellent course and helped me get my current job. My background is chemistry/chemical engineering. I had applied for a data scientist position. Phone interview included a problem where I was asked about my solution's complexity. I admitted I didn't know about it. Still got called back for an interview on site, but the weekend before I powered through this course. Unsurprisingly, it came up in the on-site…

And now in your current job how often are you evaluating the complexity and implementing specialized algorithms?

Back in 2010, I was on a team with a intake of about 1 TB per day of mapping data, all of which needed to be integrated with previous data and condensed into processed output. I quite assure you that we cared a _lot_ about the runtime complexity of our algorithms.

All the really interesting jobs require knowing data structures, algorithms and discrete mathematics well.

Re: Algorithms

#113

Post by ThrustVectoring »

apl002 wrote: post #40
koolba wrote: post #36

Earlier quoted context omitted.

If Python is the king, C is the court jester juggling knives. Done well it looks amazing, elegant, and efficient, but in the wrong hands you'll lose your hands.

Where is javascript in this medieval court?

Javascript is the kitchen hand that you taught how to chop vegetables. Yesterday you asked him to chop wood, and you've spent all of today trying to figure out why your kitchen knives are dull.

Re: Algorithms

#114

Post by b3b0p »

imakecomments wrote: post #111
b3b0p wrote: post #103

The Coursera Stanford [0] and Princeton [1] courses start again soon, February 20 to be exact. Not sure which one is better, but to refresh my atrophied CS skills of 10 years I've joined the Stanford course. Not sure how it compares to the Khan Algorithms course. Anyone have any feedback? [0] https://www.coursera.org/learn/algorithm-design-analysis/ [1] https://www.coursera.org/learn/algorithms-part1/

This is just my opinion and I'm sure it differs from others... Roughgarden's class is advance and expects mathematical maturity. You may find his course quite fast and rough if you are a beginner. Sedgwick's class is much easier. He is a bit boring and tries to use "real life" examples (in some instances) from the physical sciences to make the material relatable. This in my opinion detracts from the material. Also, h…

Great feedback and insight. Appreciated. I'll checkout the MIT OCW and Khan Academy first. I'm hardly a beginner, but my skills feel a bit rusty and want to refresh them.

Re: Algorithms

#115

Post by jeremy_wiebe »

walshemj wrote: post #80
michaelchisari wrote: post #25

Earlier quoted context omitted.

Python is the algorithm king as far as I'm concerned. It really gets out of your way and lets you focus on the abstract nature of what you're trying to accomplish.

I would have said Fortran is still the King :-)

In college I had to implement all my Data Structures coursework in COBOL. That was...interesting. :-)

Re: Algorithms

#116

Post by contravariant »

evahop wrote: post #107
contravariant wrote: post #75

Earlier quoted context omitted.

Different in what way? The general idea is that something takes O(f(n)) time if it takes at most C·f(n) time for some constant C and all but finitely many values of n. The 'all but finitely many values' is what makes this definition 'asymptotic'. Basically 'O(f(n))' ignores constant factors and the behaviour at 'small' n (i.e. small inputs), the reasoning behind this is that an algorithm in O(f(n)) is faster than any…

The information made intuitive sense to me. I just couldn't apply what was read directly to the exercises. It felt as though something crucial had been omitted. That something turns out to be calculus.

You don't technically need calculus, but knowing about limits does help.

Re: Algorithms

#117

Post by imakecomments »

b3b0p wrote: post #114
imakecomments wrote: post #111

Earlier quoted context omitted.

This is just my opinion and I'm sure it differs from others... Roughgarden's class is advance and expects mathematical maturity. You may find his course quite fast and rough if you are a beginner. Sedgwick's class is much easier. He is a bit boring and tries to use "real life" examples (in some instances) from the physical sciences to make the material relatable. This in my opinion detracts from the material. Also, h…

Great feedback and insight. Appreciated. I'll checkout the MIT OCW and Khan Academy first. I'm hardly a beginner, but my skills feel a bit rusty and want to refresh them.

No problem.

Re: Algorithms

#118

Post by kornish »

koolba wrote: post #36
michaelchisari wrote: post #25

Earlier quoted context omitted.

Python is the algorithm king as far as I'm concerned. It really gets out of your way and lets you focus on the abstract nature of what you're trying to accomplish.

If Python is the king, C is the court jester juggling knives. Done well it looks amazing, elegant, and efficient, but in the wrong hands you'll lose your hands.

There's a great book title that plays off this idea:

"Enough Rope to Shoot Yourself in the Foot: Rules for C and C++ Programming" [0]

It's also perhaps the best mixed metaphor I've ever encountered.

[0]: https://www.amazon.com/Enough-Rope-Shoot-Yourself-Foot/dp/00...

Re: Algorithms

#119

Post by sua_3000 »

imakecomments wrote: post #111
b3b0p wrote: post #103

The Coursera Stanford [0] and Princeton [1] courses start again soon, February 20 to be exact. Not sure which one is better, but to refresh my atrophied CS skills of 10 years I've joined the Stanford course. Not sure how it compares to the Khan Algorithms course. Anyone have any feedback? [0] https://www.coursera.org/learn/algorithm-design-analysis/ [1] https://www.coursera.org/learn/algorithms-part1/

This is just my opinion and I'm sure it differs from others... Roughgarden's class is advance and expects mathematical maturity. You may find his course quite fast and rough if you are a beginner. Sedgwick's class is much easier. He is a bit boring and tries to use "real life" examples (in some instances) from the physical sciences to make the material relatable. This in my opinion detracts from the material. Also, h…

I've taken both Stanford's and Princetons Coursera courses, and powered through the MIT OCW, and I would say this evaluation is spot on.

If you have to pick only one go with the MIT OCW, and snag a copy of CLRS. I got mine from my local lib. and it gave me more than enough time to work through the problem sets from the mooc.

Re: Algorithms

#120

Post by kinkrtyavimoodh »

michaelchisari wrote: post #25
tomwphillips wrote: post #23

This is an excellent course and helped me get my current job. My background is chemistry/chemical engineering. I had applied for a data scientist position. Phone interview included a problem where I was asked about my solution's complexity. I admitted I didn't know about it. Still got called back for an interview on site, but the weekend before I powered through this course. Unsurprisingly, it came up in the on-site…

Python is the algorithm king as far as I'm concerned. It really gets out of your way and lets you focus on the abstract nature of what you're trying to accomplish.

I'd disagree. Python abstracts a little too much away, and it's much easier to figure out loop ranges, invariants etc in an algorithm from say Java code.

Python works well when you have to convey your algorithm in a nice succinct functional manner, but that's optimizing for cuteness, not understanding.

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