Here's a popular text in Information Theory which goes into some detail on data compression and communication channels. Definitely a good one to read through!
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This is the fifth meet up in this series! We'll cover the first half of Chapter 5 (stopping just before Huffman Codes), and work through some problems.
Would anyone like to volunteer to present a problem? Let us know in the comments! I'll read through the problems, and suggest a few that look interesting. Feel free to do the same! We'll present solutions and discuss the material at the next meet up.
Now we're getting to the heart of the compression aspects of information theory.
• Probability theory: (moderate level) Joint distributions and marginalization; conditioning; Bayes' Theorem
• Analysis: (beginner to moderate level) Know what a set is; know what a logarithm is; understand the basic ideas of proofs by induction, contradiction, etc.
• Chapter 4: Understand the material from chapter 4 and earlier.