CS-119(d): Information, Computation, Communication

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Lectures in this course (28)

Explores dichotomy search algorithms, analyzing complexity and implementation details for efficient searching in sorted lists.

Data Compression and Shannon's Theorem Summary

Summarizes Shannon's theorem, emphasizing the importance of entropy in data compression.

Algorithmic Complexity: Theta Notation

Explores algorithmic complexity, comparing growth rates using Theta notation and characterizing different complexity classes.

Data Compression and Shannon's Theorem: Lossy Compression

Explores data compression, including lossless methods and the necessity of lossy compression for real numbers and signals.

Search Algorithms: Linear vs Logarithmic

Illustrates the efficiency of logarithmic search algorithms over linear ones, emphasizing the importance of data modeling and the trade-off between sorting and searching costs.

Conclusions on Module II

Concludes Module II by presenting two theories on optimal signal representation.

Sorting Algorithms: Sorting Methods and Comparison

Explores sorting methods, insertion sort, and algorithm comparison for efficient data organization.

Shortest Path Algorithms

Explores solving various problems as shortest path problems, including the Rubik's Cube and speech recognition.

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