算法详解 斯坦福大学经典视频课

算法详解四部曲第一卷，详解算法基础，展现算法本质，集斯坦福大学教授多年教学经验，深入浅出，通俗易懂

算法是计算机科学的核心与灵魂。算法的应用范围极广，网络路由、计算基因组学、公钥加密学和数据库系统等的实现都需要算法。研究算法可以帮助我们成为更优秀的程序员，可以让我们具有更缜密的思维，并成功应对各种场合的技术面试。

这是一本非常容易上手的算法入门图书，它可作为程序员的学习用书，也适合想要学习算法和想提升算法思维能力的读者阅读。

本书主要包括以下内容：
渐进性分析；
大O表示法；
主方法；
快速分治算法；
随机化算法；
排序算法；

选择算法。

算法是计算机科学的核心与灵魂。算法的应用范围极广，网络路由、计算基因组学、公钥加密学和数据库系统等的实现都需要算法。研究算法可以帮助我们成为更优秀的程序员，可以让我们具有更缜密的思维，并成功应对各种场合的技术面试。
这是一本非常容易上手的算法入门图书，它可作为程序员的学习用书，也适合想要学习算法和想提升算法思维能力的读者阅读。
本书主要包括以下内容：
图的搜索和应用；
散列表；
最短路径算法；
布隆过滤器；
随机化算法；
堆；
搜索树。

• 课时1：Why Study Algorithms (4分15秒)

• 课时2：Integer Multiplication (8分38秒)

• 课时3：Karatsuba Multiplication (12分39秒)

• 课时4：Merge Sort Motivation and Example (8分44秒)

• 课时5：Merge Sort Pseudocode (12分51秒)

• 课时6：Merge Sort Analysis (9分2秒)

• 课时7：Guiding Principles for Analysis of Algorithms (15分16秒)

• 课时8：The Gist (14分12秒)

• 课时9：Big Oh Notation (4分9秒)

• 课时10：Basic Examples (7分27秒)

• 课时11：Big Omega and Theta (7分31秒)

• 课时12：Additional Examples Review Optional (7分51秒)

• 课时13：On log n Algorithm for Counting Inversions I (12分35秒)

• 课时14：On log n Algorithm for Counting Inversions II (16分33秒)

• 课时15：Strassen 's Subcubic Matrix Multiplication Algorithm (22分31秒)

• 课时16：On log n Algorithm for Closest Pair I Advanced Optional (31分46秒)

• 课时17：On log n Algorithm for Closest Pair II Advanced Optional (18分58秒)

• 课时18：Motivation (7分47秒)

• 课时19：Formal Statement (9分57秒)

• 课时20：Examples (13分5秒)

• 课时21：Proof I (9分57秒)

• 课时22：Interpretation of the 3 Cases (10分46秒)

• 课时23：Proof II (16分16秒)

• 课时24：Quicksort Overview (12分8秒)

• 课时25：Partitioning Around a Pivot (24分55秒)

• 课时26：Choosing a Good Pivot (22分25秒)

• 课时27：Analysis I A Decomposition Principle Advanced Optional (21分48秒)

• 课时28：Analysis II The Key Insight Advanced Optional (11分47秒)

• 课时29：Analysis III Final Calculations Advanced Optional (8分57秒)

• 课时30：Omegan log n Lower Bound for Comparison Based Sorting Advanced Optional (13分29秒)

• 课时31：Randomized Selection Algorithm (21分39秒)

• 课时32：Randomized Selection Analysis (20分34秒)

• 课时33：Deterministic Selection Algorithm Advanced Optional (16分56秒)

• 课时34：Deterministic Selection Analysis I Advanced Optional (22分1秒)

• 课时35：Deterministic Selection Analysis II Advanced Optional (12分41秒)

• 课时36：Correctness of Quicksort Review Optional (10分38秒)

• 课时37：Part I Review Optional (25分57秒)

• 课时38：Graphs and Minimum Cuts (15分50秒)

• 课时39：Graph Representations (14分22秒)

• 课时40：Graph Search Overview (23分19秒)

• 课时41：Breadth First Search BFS The Basics (14分12秒)

• 课时42：BFS and Shortest Paths (7分43秒)

• 课时43：BFS and Undirected Connectivity (13分18秒)

• 课时44：Depth First Search DFS The Basics (7分24秒)

• 课时45：Topological Sort (21分53秒)

• 课时46：Computing Strong Components The Algorithm (29分21秒)

• 课时47：Computing Strong Components The Analysis (26分2秒)

• 课时48：Structure of the Web Optional (18分50秒)

• 课时49：Dijkstra 's Shortest Path Algorithm (20分45秒)

• 课时50：Dijkstra 's Algorithm Examples (12分45秒)

• 课时51：Correctness of Dijkstra 's Algorithm Advanced Optional (19分17秒)

• 课时52：Dijkstra 's Algorithm Implementation and Running Time (26分27秒)

• 课时53：Data Structures Overview (4分36秒)

• 课时54：Heaps Operations and Applications (18分11秒)

• 课时55：Heaps Implementation Details Advanced Optional (20分57秒)

• 课时56：Balanced Search Trees Operations and Applications (10分55秒)

• 课时57：Binary Search Tree Basics, Part I (13分7秒)

• 课时58：Binary Search Tree Basics, Part II (30分9秒)

• 课时59：Rotations Advanced Optional (7分36秒)

• 课时60：Hash Tables Operations and Applications (19分20秒)

• 课时61：Hash Tables Implementation Details, Part I (18分58秒)

• 课时62：Hash Tables Implementation Details, Part II (22分13秒)

• 课时63：Pathological Data Sets and Universal Hashing Motivation (21分54秒)

• 课时64：Bloom Filters The Basics (15分22秒)

• 课时65：Bloom Filters Heuristic Analysis (13分26秒)

• 课时66：INTRODUCTION TO GREEDY ALGORITHMS- Greedy Algorithms (12分35秒)

• 课时67：A SCHEDULING APPLICATION- Problem Definition (5分48秒)

• 课时68：A SCHEDULING APPLICATION- Greedy Algorithm (12分57秒)

• 课时69：A SCHEDULING APPLICATION- Correctness Proof - Part I (6分57秒)

• 课时70：A SCHEDULING APPLICATION- Correctness Proof - Part II (4分41秒)

• 课时71：A SCHEDULING APPLICATION- Handling Ties (7分14秒)

• 课时72：HUFFMAN CODES- Introduction and Motivation (9分19秒)

• 课时73：HUFFMAN CODES- Problem Definition (10分17秒)

• 课时74：HUFFMAN CODES- A Greedy Algorithm (16分43秒)

• 课时75：HUFFMAN CODES- A More Complex Example (4分2秒)

• 课时76：HUFFMAN CODES- Correctness Proof 1 (10分6秒)

• 课时77：HUFFMAN CODES- Correctness Proof 2 (12分46秒)

• 课时78：PRIM'S MINIMUM SPANNING TREE ALGORITHM- MST Problem Definition (11分16秒)

• 课时79：PRIM'S MINIMUM SPANNING TREE ALGORITHM- Prims MST Algorithm (7分32秒)

• 课时80：PRIM'S MINIMUM SPANNING TREE ALGORITHM- Fast Implementation 1 (14分49秒)

• 课时81：PRIM'S MINIMUM SPANNING TREE ALGORITHM- Fast Implementation 2 (9分50秒)

• 课时82：PRIM'S MINIMUM SPANNING TREE ALGORITHM- Correctness Proof 1 (15分30秒)

• 课时83：PRIM'S MINIMUM SPANNING TREE ALGORITHM- Correctness Proof 2 (8分9秒)

• 课时84：KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM- Kruskals MST Algorithm (7分27秒)

• 课时85：KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM- Implementing Kruskals Algorithm via Union Find (9分21秒)

• 课时86：KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM- Implementing Kruskals Algorithm via Union Find 2 (13分35秒)

• 课时87：ADVANCED UNION-FIND- Lazy Unions (10分3秒)

• 课时88：KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM- Correctness of Kruskals Algorithm (9分22秒)

• 课时89：CLUSTERING- Application to Clustering (11分32秒)

• 课时90：INTRODUCTION TO DYNAMIC PROGRAMMING- Introduction - Weighted Independent Sets in Path Graphs (7分55秒)

• 课时91：INTRODUCTION TO DYNAMIC PROGRAMMING- WIS in Path Graphs - Optimal Substructure (9分27秒)

• 课时92：INTRODUCTION TO DYNAMIC PROGRAMMING- WIS in Path Graphs - A Linear Time Algorithm (9分56秒)

• 课时93：INTRODUCTION TO DYNAMIC PROGRAMMING- WIS in Path Graphs - A Reconstruction Algorithm (6分53秒)

• 课时94：INTRODUCTION TO DYNAMIC PROGRAMMING- Principles of Dynamic Programming (7分57秒)

• 课时95：THE KNAPSACK PROBLEM- The Knapsack Problem (9分47秒)

• 课时96：THE KNAPSACK PROBLEM- A Dynamic Programming Algorithm (9分59秒)

• 课时97：THE KNAPSACK PROBLEM- Example (12分53秒)

• 课时98：SEQUENCE ALIGNMENT- Optimal Substructure (13分44秒)

• 课时99：SEQUENCE ALIGNMENT- A Dynamic Programming Algorithm (12分28秒)

• 课时100：OPTIMAL BINARY SEARCH TREES- Problem Definition (12分24秒)

• 课时101：OPTIMAL BINARY SEARCH TREES- Optimal Substructure (9分34秒)

• 课时102：OPTIMAL BINARY SEARCH TREES- Proof of Optimal Substructure (6分40秒)

• 课时103：OPTIMAL BINARY SEARCH TREES- A Dynamic Programming Algorithm 1 (9分45秒)

• 课时104：OPTIMAL BINARY SEARCH TREES- A Dynamic Programming Algorithm 2 (9分27秒)

• 课时105：THE BELLMAN-FORD ALGORITHM- Single-Source Shortest Paths, Revisited (10分51秒)

• 课时106：THE BELLMAN-FORD ALGORITHM- Optimal Substructure (10分46秒)

• 课时107：THE BELLMAN-FORD ALGORITHM- The Basic Algorithm 1 (8分35秒)

• 课时108：THE BELLMAN-FORD ALGORITHM- The Basic Algorithm 2 (10分55秒)

• 课时109：THE BELLMAN-FORD ALGORITHM- Detecting Negative Cycles (9分18秒)

• 课时110：ALL-PAIRS SHORTEST PATHS- Problem Definition (7分1秒)

• 课时111：ALL-PAIRS SHORTEST PATHS- Optimal Substructure (12分2秒)

• 课时112：ALL-PAIRS SHORTEST PATHS- The Floyd Warshall Algorithm (13分30秒)

• 课时113：A Field Guide to Algorithm Design (Epilogue to the Algorithms Illuminated book series) (18分46秒)

• 课时114：Overview and Prerequisites (10分4秒)

• 课时115：The Algorithmic Mystery of MST vs. TSP (16分18秒)

• 课时116：Possible Levels of Expertise (4分25秒)

• 课时117：Easy and Hard Problems (22分55秒)

• 课时118：Algorithmic Strategies for NP-Hard Problems (24分39秒)

• 课时119：A Simple Recipe for Proving NP-Hardness (26分6秒)

• 课时120：Rookie Mistakes (9分52秒)

• 课时121：Makespan Minimization Part 1 (19分17秒)

• 课时122：Makespan Minimization Part 2 (21分37秒)

• 课时123：A Greedy Heuristic for Maximum Coverage Part 1 (20分9秒)

• 课时124：A Greedy Heuristic for Maximum Coverage Part 2 (21分43秒)

• 课时125：A Greedy Heuristic for Influence Maximization 1 (19分8秒)

• 课时126：A Greedy Heuristic for Influence Maximization 2 (18分41秒)

• 课时127：The 2-OPT Heuristic for the TSP Part 1 (12分44秒)

• 课时128：The 2-OPT Heuristic for the TSP Part 2 (11分57秒)

• 课时129：Principles of Local Search Part 1 (23分11秒)

• 课时130：Principles of Local Search Part 2 (24分48秒)

• 课时131：The Bellman-Held-Karp Algorithm for TSP Part 1 (19分34秒)

• 课时132：The Bellman-Held-Karp Algorithm for TSP Part 2 (15分47秒)

• 课时133：Color Coding Part 1 (28分29秒)

• 课时134：Color Coding Part 2 (15分47秒)

• 课时135：Problem-Specific Algorithms vs. Magic Boxes (8分23秒)

• 课时136：Mixed Integer Programming Solvers (16分59秒)

• 课时137：Satisfiability Solvers (24分26秒)

• 课时138：Reductions Revisited (9分22秒)

• 课时139：SAT and the Cook-Levin Theorem (7分29秒)

• 课时140：The Big Picture (25分6秒)

• 课时141：Independent Set Is NP-Hard (27分16秒)

• 课时142：Directed Hamiltonian Path Is NP-Hard (26分24秒)

• 课时143：The TSP Is NP-Hard (12分31秒)

• 课时144：Subset Sum Is NP-Hard (26分24秒)

• 课时145：Amassing Evidence of Intractability (11分11秒)

• 课时146：Decision, Search, and Optimization (7分36秒)

• 课时147：NP- Problems with Easily Recognized Solutions (24分57秒)

• 课时148：The P!=NP Conjecture (12分4秒)

• 课时149：The Exponential Time Hypothesis (18分45秒)

• 课时150：NP-Completeness (19分17秒)

• 课时151：Repurposing Wireless Spectrum (11分15秒)

• 课时152：Greedy Heuristics for Buying Back Licenses Pt 1 (22分2秒)

• 课时153：Greedy Heuristics for Buying Back Licenses Pt 2 (14分7秒)

• 课时154：Feasibility Checking Pt 1 (17分18秒)

• 课时155：Feasibility Checking Pt 2 (26分24秒)

• 课时156：Implementation as a Descending Clock Auction (28分46秒)

• 课时157：The Final Outcome (6分11秒)

• 课时158：A Field Guide to Algorithm Design (Epilogue to the Algorithms Illuminated book series) (18分46秒)