Algorithm Mastery

Interview-style algorithms organized by priority, with specialized tracks.

Math Foundations — Many topics here build on discrete math, probability, and linear algebra. See the Math track for prerequisite material.

See Study Plan for the 21-day algorithm study plan.

Core References

Book	Access	Use For
Introduction to Algorithms (CLRS), 4th ed. — Cormen, Leiserson, Rivest, Stein	Owned (MIT Press)	Comprehensive reference for all algorithm topics; formal proofs, correctness arguments
Competitive Programmer’s Handbook — Antti Laaksonen	Free PDF	Concise implementations, contest techniques, advanced topics (segment trees, FFT)
Codeless Data Structures and Algorithms	Owned	Conceptual understanding, visual intuition
Algorithm Design Manual — Skiena	Recommended	War stories, practical algorithm selection

CLRS chapter references are noted in each topic README where applicable. For competition-focused study, see the Competitive Programming track.

Topics

#	Topic	Problems	Lang	README
01	Arrays & Hashing	Two Sum, Contains Duplicate, Product of Array Except Self, Missing Number	JS	Patterns
02	Two Pointers & Sliding Window	3Sum, Container With Most Water	JS	Patterns
03	Binary Search	Find Min in Rotated Array, Search in Rotated Array, LISS	JS	Patterns
04	Linked Lists	Add Two Numbers	JS	Patterns
05	Trees	AVL Tree + Range Query	Python	Patterns
06	Graphs	Clone Graph, Course Schedule, Number of Islands, Pacific Atlantic Water Flow, Corgi Conundrum	JS/TS/C	Patterns
07	Dynamic Programming	Climbing Stairs, House Robber, House Robber II, Coin Change, Unique Paths, Decode Ways, Word Break, Max Subarray, Max Product Subarray, LCS, Knapsack, Edit Distance, Kadane, DP on Graph, Optimal BST, Probabilistic Transitions, Alignment	JS/Python/C	Patterns
08	Greedy	Best Time to Buy/Sell Stock, Jump Game, Example 1, Example 2, Example 3, Huffman Coding	JS/Python/Java	Patterns
09	Backtracking	Combination Sum, Map Coloring	JS/Python	Patterns
10	Math & Bit Manipulation	Count Bits, Number of 1 Bits, Reverse Bits, Sum of Two Integers	JS	Patterns
11	Recursion & Divide-and-Conquer	Tree Path, Max Subarray D&C	Python	Patterns
15	Probabilistic Structures	Bloom Filter	Python	Patterns
16	Systems Data Structures	Course modules ds.01 to ds.09: Swiss and Robin Hood hash maps, heaps and top-k, LRU, radix tree, Bloom filter, bounded-load consistent hashing	C/Rust/Go	Patterns

Topics 12 to 14 were historical coursework (a C miner, Scheme exercises, ML and NLP labs) and moved to archive/algorithms/; the numbers stay reserved so links and the study plan keep their order. Topics 01 to 11 and 15 are the interview-pattern chapters (off the course spine, used by the interview drills); topic 16 hosts course modules.

Interviews

Company-specific interview guides covering focus areas, question styles, and preparation strategies.

See interviews/README.md for the full breakdown.

Practice

Standalone implementations for hands-on practice.

See practice/ for exercises. The K-Means clustering and TF-IDF vector search scripts are archived in archive/algorithms/14-ml-statistics/, where the course cites them as worked examples for ag.07.