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Encounter with Algorithms
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Divide and conquer
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Backtracking
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Dynamic programming
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Greedy
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Data structures and algorithms crash course with animated illustrations and off-the-shelf code
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500 animated illustrations, 14 programming languages, and 3000 community Q& As to help you quickly get started with data structures and algorithms
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Paperbook
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Read online
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Download PDF
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Endorsements
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“An easy-to-understand book on data structures and algorithms, which guides readers to learn by minds-on and hands-on. Strongly recommended for algorithm beginners!”
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—— Junhui Deng, Professor, Department of computer science and technology, Tsinghua University
< / p >
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< div class = "intro-text endor-text" >
< p style = "margin-bottom: 0;" >
“If I had 'Hello Algo' when I was learning data structures and algorithms, it would have been 10 times easier!”
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< p style = "font-weight: bold;" >
—— Mu Li, Senior principal scientist, Amazon
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Animated illustrations
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It's crafted for ease of understanding, ensuring a smooth learning journey.
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"A picture is worth a thousand words."
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Off-the-shelf code
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Featuring multiple programming languages, all runnable with a single click.
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"Talk is cheap. Show me the code."
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Learning together
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Welcome discussions and questions with open arms.
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< p class = "intro-quote" >
"Learning by teaching."
< / p >
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< / div >
< img alt = "Comments example" class = "intro-image" src = "index.assets/comment.gif" / >
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< h3 >
Author
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< div class = "profile-div" >
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< a href = "https://github.com/krahets" >
< img alt = "Author: yudongjin" class = "profile-img" src = "../assets/avatar/avatar_yudongjin.jpg" / >
< br / >
< b >
Yudong Jin（ ）
< / b >
< / a >
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< / div >
< / div >
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Code reviewers
< / h3 >
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< a href = "https://github.com/codingonion" >
< img alt = "Reviewer: codingonion" class = "profile-img" src = "../assets/avatar/avatar_codingonion.jpg" / >
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codingonion
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< br / >
< sub >
Zig, Rust
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< a href = "https://github.com/curtishd" >
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curtishd
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Kotlin
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< a href = "https://github.com/Gonglja" >
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Gonglja
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C, C++
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< a href = "https://github.com/gvenusleo" >
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gvenusleo
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Dart
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hpstory
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C#
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< a href = "https://github.com/justin-tse" >
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justin-tse
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JS, TS
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krahets
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Python, Java
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< a href = "https://github.com/night-cruise" >
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< br / >
< b >
night-cruise
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< br / >
< sub >
Rust
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< / a >
< / div >
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< a href = "https://github.com/nuomi1" >
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< br / >
< b >
nuomi1
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< sub >
Swift
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< a href = "https://github.com/Reanon" >
< img alt = "Reviewer: Reanon" class = "profile-img" src = "../assets/avatar/avatar_Reanon.jpg" / >
< br / >
< b >
Reanon
< / b >
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Go, C
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< / div >
< / div >
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< h3 >
Contributors
< / h3 >
< p >
This book has been enhanced through the collaborative efforts of more than 100 contributors. Thanks for their invaluable time and input!
< / p >
< a href = "https://github.com/krahets/hello-algo/graphs/contributors" >
< img alt = "Contributors" src = "https://contrib.rocks/image?repo=krahets/hello-algo&max=300&columns=16" style = "width: 100%; max-width: 38.5em;" / >
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Hello Algo
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Before starting
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Chapter 0. Preface
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Chapter 0. Preface
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0.1 About this book
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0.2 How to read
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0.3 Summary
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Chapter 1. Encounter with algorithms
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Chapter 1. Encounter with algorithms
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1.1 Algorithms are everywhere
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1.2 What is an algorithm
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1.3 Summary
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Chapter 2. Complexity analysis
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Chapter 2. Complexity analysis
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2.1 Algorithm efficiency assessment
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2.2 Iteration and recursion
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2.3 Time complexity
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2.4 Space complexity
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2.5 Summary
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Chapter 3. Data structures
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Chapter 3. Data structures
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3.1 Classification of data structures
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3.2 Basic data types
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3.3 Number encoding *
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3.4 Character encoding *
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3.5 Summary
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Chapter 4. Array and linked list
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Chapter 4. Array and linked list
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4.1 Array
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4.2 Linked list
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4.3 List
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4.4 Memory and cache *
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4.5 Summary
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Chapter 5. Stack and queue
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Chapter 5. Stack and queue
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5.1 Stack
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5.2 Queue
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5.3 Double-ended queue
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5.4 Summary
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Chapter 6. Hash table
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Chapter 6. Hash table
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6.1 Hash table
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6.2 Hash collision
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6.3 Hash algorithm
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6.4 Summary
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Chapter 7. Tree
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Chapter 7. Tree
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7.1 Binary tree
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7.2 Binary tree traversal
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7.3 Array Representation of tree
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7.4 Binary Search tree
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7.5 AVL tree *
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7.6 Summary
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Chapter 8. Heap
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Chapter 8. Heap
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8.1 Heap
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8.2 Building a heap
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8.3 Top-k problem
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8.4 Summary
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Chapter 9. Graph
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Chapter 9. Graph
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9.1 Graph
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9.2 Basic graph operations
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9.3 Graph traversal
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9.4 Summary
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Chapter 10. Searching
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Chapter 10. Searching
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10.1 Binary search
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10.2 Binary search insertion
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10.3 Binary search boundaries
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10.4 Hashing optimization strategies
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10.5 Search algorithms revisited
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10.6 Summary
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Chapter 11. Sorting
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Chapter 11. Sorting
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11.1 Sorting algorithms
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11.2 Selection sort
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11.3 Bubble sort
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11.4 Insertion sort
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11.5 Quick sort
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11.6 Merge sort
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11.7 Heap sort
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11.8 Bucket sort
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11.9 Counting sort
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11.10 Radix sort
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11.11 Summary
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Chapter 12. Divide and conquer
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Chapter 12. Divide and conquer
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12.1 Divide and conquer algorithms
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12.2 Divide and conquer search strategy
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12.3 Building binary tree problem
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12.4 Tower of Hanoi Problem
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12.5 Summary
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Chapter 13. Backtracking
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Chapter 13. Backtracking
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13.1 Backtracking algorithms
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13.2 Permutation problem
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13.3 Subset sum problem
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13.4 n queens problem
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13.5 Summary
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Chapter 14. Dynamic programming
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14.1 Introduction to dynamic programming
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14.2 Characteristics of DP problems
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14.3 DP problem-solving approach¶
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14.4 0-1 Knapsack problem
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14.5 Unbounded knapsack problem
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14.6 Edit distance problem
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14.7 Summary
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Chapter 15. Greedy
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15.1 Greedy algorithms
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15.2 Fractional knapsack problem
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15.3 Maximum capacity problem
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15.4 Maximum product cutting problem
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15.5 Summary
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Chapter 16. Appendix
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16.1 Installation
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16.2 Contributing
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