Enjoyable Blog of Possibilities

Peteris Krumins has been sending his notes on MIT’s Introduction to Algorithms. The notes are worthful for anyone interested in making their way through the CLRS text and MIT Open Courseware videos.

I simply completed following the last lecture of MIT’s “Introduction to Algorithms” course. Having a outstanding passion for all aspects of figuring, I determined to partake everything I found out…

Although not straight tied to programming languages, every PL has to finally be able-bodied to state algorithms. Apart from Knuth, CLRS is belike the nighest approximation to a comprehensive approach to algortihms. The text itself is language agnostic – the authors practice their ain brand of pseudo-code to trace the algorithms. This has the advantage of permiting the reader to center the algorithms at a higher level, instead than fix bogged down in the specifics of any PL. The downside, at least in my estimation, is that the authors don”t make it particularly easy to implement the algorithms in any specific PL. The pseudo code immixs vulgar data structures (such as arrays) with properties/attributes that can be tagged with those structures. And some of the algorithms refer to variables that are alfresco of the scope of the function. Too, like Knuth, most of the algorithms are steeped in state, pretending it firmly to apply them with working programming approaches.

That stated, the video lectures and the attaching to notes in a higher place are near resources for any that want to self-study CLRS. Hither are the notes hence far:

• Lectures 1 and 2: Analysis of Algorithms
• Lecture 3: Part and Conquer
• Lectures 4 and 5: Separating
• Lecture 6: Order Statistics
• Lectures 7 and 8: Hashing
• Lectures 9 and 10: Search Trees
• Lecture 11: Augmenting Data Structures
• Lecture 12: Skip Lists

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