Solution explanation and walkthrough for Ch 5, Problem 23.

Error in the Algorithm Design Manual?

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Computer Science: Mistake in the Algorithm Design Manual?

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Introduction to algorithms aka CLRS is a great book for people who are interested in learning the basic computer science algorithms in detail, but the book is also scary due to its exhaustiveness and heavy use of mathematics.

In this video, I will tell you about two (or three) tips about how to go about learning algorithms from this book efficiently. Let's begin.
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This video is Part - 1 of
Algorithms, Flowcharts, Introduction to Problem Solving

Algorithm and Flowchart for Beginners ,
Introduction to Problem Solving, Algorithm Tutorial for Beginners
Flowchart for class 9 ,
Introduction to problem solving Class 11,
Algorithm Tutorial for Beginners in Hindi

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Learn how to use Dynamic Programming in this course for beginners. It can help you solve complex programming problems, such as those often seen in programming interview questions about data structures and algorithms.

This course was developed by Alvin Zablan from Coderbyte. Coderbyte is one of the top websites for technical interview prep and coding challenges.

🔗 Check out the Coderbyte channel: youtube.com/channel/UCOJtQcnBnIy4LERo6vkrItg
🔗 Improve your coding and interview skills: coderbyte.com/member?promo=janpromo4351&utm_source=FCC&utm_medium=Video&utm_campaign=promo&utm_content=Dynamic%20Programming (NOT an affiliate link)

This course uses images and animations to help you visualize problems and important concepts. After understanding problems conceptually, you will learn how to solve them in JavaScript using Dynamic Programming. Even though JavaScript is used in this course, you will learn concepts and knowledge that you can apply to other programming languages.

⭐️ Course Contents ⭐️
⌨️ (00:00:00) course introduction
⌨️ (00:03:30) fib memoization
⌨️ (00:38:39) gridTraveler memoization
⌨️ (01:04:52) memoization recipe
⌨️ (01:09:56) canSum memoization
⌨️ (01:29:29) howSum memoization
⌨️ (01:52:06) bestSum memoization
⌨️ (02:12:45) canConstruct memoization
⌨️ (02:38:36) countConstruct memoization
⌨️ (02:47:30) allConstruct memoization
⌨️ (03:10:53) fib tabulation
⌨️ (03:22:17) gridTraveler tabulation
⌨️ (03:34:32) tabulation recipe
⌨️ (03:37:59) canSum tabulation
⌨️ (03:53:01) howSum tabulation
⌨️ (04:07:21) bestSum tabulation
⌨️ (04:20:50) canConstruct tabulation
⌨️ (04:38:06) countConstruct tabulation
⌨️ (04:50:23) allConstruct tabulation
⌨️ (05:07:44) closing thoughts

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C++ Data Structures and Algorithm Design Principles Course

This is C++ Data Structures and Algorithm Design Principles training course for beginners. In this course you will learn about core data structure concepts like linked list, array, queue, stack and etc. We have covered each topic from linked list to dynamic programming and we have explained it briefly.
1. Linked Lists 2:46
2. std::array 9:10
3. std::vector 16:49
4. std:: forward list 27:57
5. std::list 34:12
6. std::deque 40:27
7. std::Stack 45:14
8. std::Queue 50:42
9. std::Priority Queue 54:17
10. What is Heap and how to implement in C++ 58:08
11. hash Table Theory 1:08:36
12. Managing Hash Table Collisons 1:17:27
13. How to use C++ Hash tables in STL 1:24:48
14. What is a bloom filter, and how to create one 1:27:56
15. Merge Sort vs Quick Sort 1:38:25
16. C++ STL Binary Search and Sort methods 1:48:11
17. What is a greedy algorithm? 1:53:26
18. What is a graph, vertices and edges 1:58:25
19. Breadth first search 2:02:21
20. Depth first search 2:06:53
21. What is dynamic programming? 2:10:06

Bridge the gap between high-level system models and detailed design models, providing a unified modelling environment and enabling models to serve as a single source of truth throughout the design lifecycle. In this session, our Solutions Engineer will walk you through the capabilities and features that assist with supporting systems engineering activities, which include requirements engineering and systems architecting.

Holger Hoos, Frank Hutter (Part 2)
Programming by Optimization: A Practical Paradigm for Computer-Aided Algorithm Design
213, Melbourne Convention Centre, Mon AM, Aug 21 2017

ktu S6 CS 302 - module 1

A beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python. This course will help you prepare for coding interviews and assessments.

🔗 Course website: jovian.ai/learn/data-structures-and-algorithms-in-python

✏️ Created by Aakash N S, founder and CEO of Jovian.

⭐️ Course Lessons with Code ⭐️
🟢 Lesson 1 - Binary Search, Linked Lists and Complexity
💻 Linear and Binary Search: jovian.ai/aakashns/python-binary-search
💻 Problem Solving Template: jovian.ai/aakashns/python-problem-solving-template
💻 Linked Lists in Python: jovian.ai/aakashns/python-classes-and-linked-lists
🟢 Assignment 1 - Binary Search Practice
💻 Starter Notebook: jovian.ai/aakashns/python-binary-search-assignment
🟢 Lesson 2 - Binary Search Trees, Traversals and Recursion
💻 Binary Search Trees in Python: jovian.ai/aakashns/python-binary-search-trees
💻 Problem Solving Template: jovian.ai/aakashns/python-problem-solving-template
💻 Linked Lists in Python: jovian.ai/aakashns/python-classes-and-linked-lists
🟢 Assignment 2 - Hash Tables and Python Dictionaries
💻 Starter Notebook: jovian.ai/aakashns/python-hash-tables-assignment
🟢 Lesson 3 - Sorting Algorithms and Divide & Conquer
💻 Sorting and Divide & Conquer: jovian.ai/aakashns/python-sorting-divide-and-conquer
💻 Problem Solving Template: jovian.ai/aakashns/python-problem-solving-template
🟢 Assignment 3 - Divide and Conquer Practice
💻 Starter Notebook: jovian.ai/aakashns/python-divide-and-conquer-assignment
🟢 Lesson 4 - Recursion and Dynamic Programming
💻 Problem-solving template: jovian.ai/aakashns/python-problem-solving-template
💻 Dynamic Programming problems: jovian.ai/aakashns/dynamic-programming-problems
🟢 Lesson 5 - Graph Algorithms (BFS, DFS & Shortest Paths)
💻 Graphs and Graph Algorithms (Starter Notebook): jovian.ai/aakashns/python-graph-algorithms
🟢 Project - Step-by-Step Solution to a Programming Problem
💻 Starter Notebook: jovian.ai/aakashns/python-problem-solving-template
🟢 Lesson 6 - Python Interview Questions, Tips & Advice
💻 Problem solving template: jovian.ai/aakashns/python-problem-solving-template
💻 Coding problem 1: jovian.ai/aakashns/python-subarray-with-given-sum
💻 Coding problem 2: jovian.ai/aakashns/python-minimum-edit-distance

⭐️ Course Contents ⭐️
⌨️ (00:00:00) Introduction
⌨️ (00:01:43) Binary Search Linked Lists and Complexity
⌨️ (00:03:43) Introduction
⌨️ (00:08:35) Problem
⌨️ (00:12:17) The Method
⌨️ (00:13:55) Solution
⌨️ (00:50:52) Complexity and Big O notation
⌨️ (01:24:57) Binary Search vs Linear Search
⌨️ (01:31:40) Generic Binary Search
⌨️ (01:40:08) Summary and Conclusion
⌨️ (01:44:30) Assignment Walkthrough
⌨️ (01:45:05) Introduction
⌨️ (01:50:01) Problem- Rotated Lists
⌨️ (01:53:02) The Method
⌨️ (01:54:03) Solution
⌨️ (02:30:47) Summary and Conclusion
⌨️ (02:33:29) Binary Search Trees Python Tutorial
⌨️ (02:34:41) Introduction
⌨️ (02:37:36) Problem
⌨️ (02:38:40) The Method
⌨️ (03:13:58) Binary tree
⌨️ (03:27:16) Traversing Binary Tree
⌨️ (03:36:10) Binary Search Tree
⌨️ (04:22:37) Self-Balancing Binary Trees and AVL Trees
⌨️ (04:26:27) Summary and Conclusion
⌨️ (04:30:33) Hash Tables and Python Dictionaries
⌨️ (04:31:09) Introduction
⌨️ (04:34:00) Problem
⌨️ (04:40:28) Data List
⌨️ (04:42:52) Hash Function
⌨️ (04:54:52) Basic Hash Table Implementation
⌨️ (05:03:07) Handling Collisions with Linear Probing
⌨️ (05:09:24) Summary and Conclusion
⌨️ (05:16:47) Sorting Algorithms and Divide & Conquer
⌨️ (05:17:48) Introduction
⌨️ (05:20:19) Problem
⌨️ (05:21:27) The Method
⌨️ (06:40:49) Custom Comparison Functions
⌨️ (06:48:53) Summary and Conclusion
⌨️ (06:54:57) Recursion Memoization & Dynamic Programming
⌨️ (06:56:37) Introduction
⌨️ (07:00:04) Problem
⌨️ (07:04:28) The Method
⌨️ (07:06:21) Solution
⌨️ (08:06:13) Knapsack Problems
⌨️ (08:08:48) The Method
⌨️ (08:09:24) Solution
⌨️ (08:43:26) Summary and Conclusion
⌨️ (08:44:05) Graph Algorithms BFS, DFS & Shortest Paths
⌨️ (08:45:02) Introduction
⌨️ (08:51:00) Graph Data Structure
⌨️ (09:15:57) Graph Algorithms - Breadth-First Search
⌨️ (09:37:28) Depth-First Search
⌨️ (10:08:26) Shortest Paths
⌨️ (10:40:39) Summary and Conclusion
⌨️ (10:42:21) Python Interview Questions Tips & Advice
⌨️ (10:43:09) Introduction
⌨️ (10:44:08) The Method
⌨️ (10:47:10) Solution
⌨️ (12:30:51) Summary and Conclusion

The technical interview is a crucial part of landing a job at some of the top tech companies like Google, Facebook, Amazon, Microsoft, etc. The format is not perfect, but it's a reasonable way for companies to assess your domain knowledge in core computer science topics like data structures and algorithms. 

In this video, I show my top 5 books that have helped me be more effective at technical interviewing. If you're preparing for interviews yourself, I hope you find some useful content within this video.

Cracking the Coding Interview:
amzn.to/2E5KVZc

Elements of Programming Interviews (Python):
amzn.to/2E49Gog

Programming Interviews Exposed:
amzn.to/2SFUshr

The Algorithm Design Manual:
amzn.to/2I2Z7px

Introduction to Algorithms (3rd Edition):
amzn.to/2WWyHth

Data Structures:
bit.ly/lp_data_structures

Algorithms:
bit.ly/lp_algos

Technical Interview Problems:
bit.ly/lp_technical_interview

Slide Deck:
docs.google.com/presentation/d/1FZkFcAvnmxMQ1XYHpruBkkovg95ef-pVweY6m5M5pu4/edit?usp=sharing

8/24/21

Finding Time Complexity of Different kind of snippets

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C++ Programming
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Introduction to Backtracking

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C++ Programming
udemy.com/course/cpp-deep-dive/?referralCode=E4246A516919D7E84225

Algorithm Design Manual Question

Helpful? Please support me on Patreon: patreon.com/roelvandepaar

With thanks & praise to God, and with thanks to the many people who have made this project possible! | Content (except music & images) licensed under CC BY-SA meta.stackexchange.com/help/licensing | Music: bensound.com/licensing | Images: stocksnap.io/license & others | With thanks to user Yuval Filmus (cs.stackexchange.com/users/683), user user1477539 (cs.stackexchange.com/users/35125), and the Stack Exchange Network (cs.stackexchange.com/questions/45274). Trademarks are property of their respective owners. Disclaimer: All information is provided "AS IS" without warranty of any kind. You are responsible for your own actions. Please contact me if anything is amiss at Roel D.OT VandePaar A.T gmail.com

TOC: Turing Machine (Example-1)
Topics discussed:
This lecture shows how to design a Turing Machine for the language 01*0

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Hi

Recently CSES added 100 new problems to their problemset. Here is the
solution to one those problems from the dynamic programming section.

cses.fi/problemset/task/2413/

The solution discussed in the video is O(N) per testcase and overall has a time complexity of O(N*T).
However it is possible to cache the results beforehand thus answering each query in O(1) and get an improved running time of O(N+T).
Here is the optimized code: cses.fi/paste/e643e2acd0c927841739f2/

Do support the channel by hitting the subscribe button and giving a like :)
Super useful books for algo ds and programming fundamentals!

1. Introduction to Algorithms by Cormen: amzn.to/35AmQqu
2. The Algorithm Design Manual: amzn.to/2K9RGPq
3. Fundamentals of Data Structures in C++: amzn.to/2LCwIsN
4. Object-Oriented Programming by E Balagurusamy: amzn.to/2Xxmdtr
5. Head First Java: amzn.to/39kb44K
6. Cracking the coding interview: amzn.to/3iDOHLK
7. Database System concepts: amzn.to/3pisuFQ
8. Operating Systems: amzn.to/39fcmis
9. Discrete Mathematics: amzn.to/2MlgCE6
10. Compiler Design: amzn.to/3pkYvx2

Referred:
- Introduction to Algorithms, 3rd ed. by Thomas H. Cormen et al, chapter 3
- The Algorithm Design Manual, 2nd ed, by Steven S. Skiena, chapter 2.2, 2.3, 2.4
- dcc.fc.up.pt/~pribeiro/aulas/alg1819/slides/2_asymptoticanalysis_02102018.pdf
- course.ccs.neu.edu/cs5002f18-seattle/lects/cs5002_lect9_fall18_notes.pdf