Lectures and Recitations
From 6.006 Introduction to Algorithms
- Lecture 1, Introduction and Document Distance
- Document Distance (docdist{1,2,3,4}.py)
- Readings: CLRS, Chapters 1, 2, 3.
- Recitation 1, Document Distance in Python (docdist{1,2,3,4}.py)
- Victor's Slides [PDF] | [Zipped Keynote]
- Lecture 2, More Document Distance, Mergesort
- Document Distance (docdist{5,6}.py)
- Readings: CLRS, Sections 11.1 and 11.2.
- Recitation 2, Python Cost Model, Review for Asymptotic Notation & Mergesort
- Victor's Slides [PDF] | [Zipped Keynote] | [Zipped Data (Numbers)]
- Python Cost Model
- Lecture 3, Airplane scheduling; Binary Search Trees
- Binary Search Trees (including code)
- Readings: CLRS, Chapter 10 and Sections 12.1-12.3
- Recitation 3, Binary Search Trees
- Victor's Slides [PDF] | [Zipped Keynote]
- Code for Binary Search Trees augmented with subtree size [Python]
- Lecture 4, Balanced Binary Search Trees
- See Binary Search Trees for AVL code
- Readings: CLRS, Sections 13.1 and 13.2 for a different approach (red-black trees)
- AVL tree animation applet
- Recitation 4, AVL Trees (Balanced Binary Search Trees)
- Hueihan's Slides [PDF ]
- Victor's Slides [PDF] | [Zipped Keynote]
- Code for AVL Trees: coming as soon as Victor fixes his version
- Lecture 5, Hashing I: Chaining, Hash Functions
- Document Distance (docdist-dict.py)
- Recitation 5 Hashing in Python, Mutability
- Hueihan's Slides [PDF ]
- Victor's Slides [PDF] | [Zipped Keynote]
- Lecture 6, Hashing II: Table Doubling, Karp-Rabin
- Reading: CLRS, Chapter 17 and Section 32.2
- Lecture 7, Hashing III: Open Addressing
- Reading: CLRS, Section 11.4 (and 11.3.3 and 11.5 if interested)
