算法详解 斯坦福大学经典视频课
共158课时 1天14小时39分27秒秒
简介
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;
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。
章节
- 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)
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