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Related lectures (11)
Decision Trees: Induction and Pruning
Explores Decision Trees, from induction to pruning, emphasizing interpretability and automatic feature selection strengths, while addressing challenges like overfitting.
Kraft-McMillan Theorem
Explores the Kraft-McMillan theorem, proving the existence of uniquely decodable prefix-free codes.
Compression: Kraft Inequality
Explains compression and Kraft inequality in codes and sequences.
Source Coding: Compression
Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.
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.
Data Compression and Shannon's Theorem: Shannon-Fano Coding
Explores Shannon-Fano coding for efficient data compression and its comparison to Huffman coding.
Data Compression and Shannon's Theorem: Huffman Codes
Explores the performance of Shannon-Fano algorithm and introduces Huffman codes for efficient data compression.