Data Compression: Concepts and Techniques

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Related lectures (30)

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Data Compression and Shannon-Fano Algorithm

Explores the Shannon-Fano algorithm for data compression and its efficiency in creating unique binary codes for letters.

Data Compression and Entropy: Basics and Introduction

Introduces data compression, entropy, and the importance of reducing redundancy in data.

PCA: Directions of Largest Variance

Covers PCA, finding directions of largest variance, data dimensionality reduction, and limitations of PCA.

Mohr Circle: Stress Analysis

Explains stress analysis using Mohr circles and strain energy concepts.

Compression: Prediction

Covers the concepts of compression and prediction using prefix-free codes and distributions.

Model Compression: Techniques for Efficient NLP Models

Explores model compression techniques in NLP, discussing pruning, quantization, weight factorization, knowledge distillation, and attention mechanisms.

Data Compression and Entropy: Compression

Explores lossless data compression techniques, emphasizing efficient message representation and encoding strategies.

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.

Video Compression: Standards & Techniques

Explores the evolution of video compression standards and techniques, from H.261 to VVC, emphasizing advancements in compression efficiency and video quality.

Data Compression and Entropy 2: Entropy as 'Question Game'

Explores entropy as a 'question game' to guess letters efficiently and its relation to data compression.