Dynamic Programming for the Day Before Your Coding Interview PDF Download
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Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 52
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Book Description
Dynamic Programming is a fundamental algorithmic technique which is behind solving some of the toughest computing problems.In this book, we have covered some Dynamic Programming problems which will give you the general idea of formulating a Dynamic Programming solution and some practice on applying it on a variety of problems.Some of the problems we have covered are: * Permutation coefficientThis is a basic problem but is significant in understanding the idea behind Dynamic Programming. We have used this problem to: * Present the two core ideas of Dynamic Programming to make the idea clear and help you understand what Dynamic Programming mean. * Show another approach which can same performance (in terms of time complexity) and understand how it is different from our Dynamic Programming approach* Longest Common SubstringThis is an important problem as we see how we can apply Dynamic Programming in string problems. In the process, we have demonstrated the core ideas of handling string data which helps in identifying the cases when Dynamic Programming is the most efficient approach.* XOR valueThis is another significant problem as we are applying Dynamic Programming on a Number Theory problem more specifically problem involving subset generation. The search space is exponential in size but with our efficient approach, we can search the entire data in polynomial time which is a significant improvement.This brings up a fundamental power of Dynamic Programming: Search exponential search space in polynomial time* K edgesIn line with our previous problems, in this problem, we have applied Dynamic Programming in a graph-based problem. This is a core problem as in this we learn that: * Dynamic Programming makes the solution super-efficient * Extending the Dynamic Programming solution using Divide and Conquer enables us to solve it more efficientlyThis problem shows a problem where Dynamic Programming is not the most efficient solution but is in the right path.We have covered other relevant solutions and ideas as well so that you have the complete idea of the problems and understand deeply the significance of Dynamic Programming in respect to the problems.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from professors at The University of Tokyo and Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.
Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 52
Get Book Here
Book Description
Dynamic Programming is a fundamental algorithmic technique which is behind solving some of the toughest computing problems.In this book, we have covered some Dynamic Programming problems which will give you the general idea of formulating a Dynamic Programming solution and some practice on applying it on a variety of problems.Some of the problems we have covered are: * Permutation coefficientThis is a basic problem but is significant in understanding the idea behind Dynamic Programming. We have used this problem to: * Present the two core ideas of Dynamic Programming to make the idea clear and help you understand what Dynamic Programming mean. * Show another approach which can same performance (in terms of time complexity) and understand how it is different from our Dynamic Programming approach* Longest Common SubstringThis is an important problem as we see how we can apply Dynamic Programming in string problems. In the process, we have demonstrated the core ideas of handling string data which helps in identifying the cases when Dynamic Programming is the most efficient approach.* XOR valueThis is another significant problem as we are applying Dynamic Programming on a Number Theory problem more specifically problem involving subset generation. The search space is exponential in size but with our efficient approach, we can search the entire data in polynomial time which is a significant improvement.This brings up a fundamental power of Dynamic Programming: Search exponential search space in polynomial time* K edgesIn line with our previous problems, in this problem, we have applied Dynamic Programming in a graph-based problem. This is a core problem as in this we learn that: * Dynamic Programming makes the solution super-efficient * Extending the Dynamic Programming solution using Divide and Conquer enables us to solve it more efficientlyThis problem shows a problem where Dynamic Programming is not the most efficient solution but is in the right path.We have covered other relevant solutions and ideas as well so that you have the complete idea of the problems and understand deeply the significance of Dynamic Programming in respect to the problems.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from professors at The University of Tokyo and Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.
Author: Meenakshi
Publisher: Notion Press
ISBN: 194655670X
Category : Computers
Languages : en
Pages : 168
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Book Description
I wanted to compute 80th term of the Fibonacci series. I wrote the rampant recursive function, int fib(int n){ return (1==n || 2==n) ? 1 : fib(n-1) + fib(n-2); } and waited for the result. I wait… and wait… and wait… With an 8GB RAM and an Intel i5 CPU, why is it taking so long? I terminated the process and tried computing the 40th term. It took about a second. I put a check and was shocked to find that the above recursive function was called 204,668,309 times while computing the 40th term. More than 200 million times? Is it reporting function calls or scam of some government? The Dynamic Programming solution computes 100th Fibonacci term in less than fraction of a second, with a single function call, taking linear time and constant extra memory. A recursive solution, usually, neither pass all test cases in a coding competition, nor does it impress the interviewer in an interview of company like Google, Microsoft, etc. The most difficult questions asked in competitions and interviews, are from dynamic programming. This book takes Dynamic Programming head-on. It first explain the concepts with simple examples and then deep dives into complex DP problems.
Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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Book Description
Graph Algorithms are fundamentally important and different than other Algorithmic domains as it gives an inherent structure to the data and we operate on it. This is one of the most important domains for Coding Interviews focused on problem solving.Following are some of the problems we have explored which involve ideas to solve a wider range of problems: - All paths between two verticesThis is a fundamental problem as modifications to it results in solving a wide range of problems. In the process of formulating a solution, we have explored core ideas like graph traversal techniques like Depth First Search and Graph representation like Adjacency List.- Mother VertexThis is an important problem as it highlights two key ideas of Graph problems that is connectivity and importance of specific vertices.We have solved this problem using two approaches where the efficient approach is a modification of Depth First Search and takes O(V^2) time complexity.- Paths with K edgesThis is an important problem as it demonstrates how we can utilize ideas from Dynamic Programming and Divide and Conquer to solve Graph Problems.We have demonstrated four approaches where the brute force approach takes O(2^V x V) time, improving it with a structure we get to O(V^K) time, further applying Dynamic Programming to it, we get to O(V^3 * K) time and finally, using Divide and Conquer to optimize calculation, we arrive at O(V^3 * logK) time.This is a perfect Graph Algorithm problem.We have covered more variants of the problems and ideas in our conclusion to give a bigger picture and better equip you to solve any problem.With these problems and the thought process to solve them, you will be fully prepared.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from professors at The University of Tokyo and Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.Books in this series ("Day before coding Interview"): - Problems for the day before your coding interview- Greedy Algorithms for the day before your Coding Interview- Dynamic Programming for the day before your coding interview- String Algorithms for the day before your Coding Interview- Mathematical Algorithms for the day before your Coding Interview- Graph Algorithms for the day before your Coding Interview
Author: Gayle Laakmann McDowell
Publisher: CreateSpace
ISBN: 9781466208681
Category : Computer programmers
Languages : en
Pages : 0
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Book Description
Now in the 5th edition, Cracking the Coding Interview gives you the interview preparation you need to get the top software developer jobs. This book provides: 150 Programming Interview Questions and Solutions: From binary trees to binary search, this list of 150 questions includes the most common and most useful questions in data structures, algorithms, and knowledge based questions. 5 Algorithm Approaches: Stop being blind-sided by tough algorithm questions, and learn these five approaches to tackle the trickiest problems. Behind the Scenes of the interview processes at Google, Amazon, Microsoft, Facebook, Yahoo, and Apple: Learn what really goes on during your interview day and how decisions get made. Ten Mistakes Candidates Make -- And How to Avoid Them: Don't lose your dream job by making these common mistakes. Learn what many candidates do wrong, and how to avoid these issues. Steps to Prepare for Behavioral and Technical Questions: Stop meandering through an endless set of questions, while missing some of the most important preparation techniques. Follow these steps to more thoroughly prepare in less time.
Author: Aditya Chatterjee
Publisher: OpenGenus
ISBN:
Category : Computers
Languages : en
Pages : 46
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Book Description
Become Dynamic Programming Master in 7 days Do share your review with us. It will help us help you better. 👌 Dynamic Programming is one of the most important algorithmic domains and is equally challenging. With practice and correct way of thinking, you can master it easily. If a problem takes O(2^N) time to search a solution among possible solutions, Dynamic Programming has the potential to reduce it to O(N) or polynomial time thereby reducing the search space. We will attempt one problem every day in this week and analyze the problem deeply. Our schedule: • Day 1: Introduction + Longest Increasing Subsequence • Day 2: 2D version of Day 1 problems • Day 3: Dynamic Programming on Strings • Day 4: Modified version of Day 3 problems • Day 5: Dynamic Programming for String patterns (Longest Palindromic Substring) • Day 6: Modified version of Day 4 problems • Day 7: 2 conditions on 1 data point On following this routine sincerely, you will get a strong hold on Dynamic Programming and will be able to attempt interview and real-life problems easily. #7daysOfAlgo: a 7-day investment to Algorithmic mastery.
Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
Strings are fundamental data type in real world and developing algorithms to deal with it is an important domain. In interviews, often, string algorithms are most insightful and challenging.In this guide for the day before your coding interview, we have explored some problems and demonstrated the thought process to solve it starting from the brute force solutions. In the process, we have covered all fundamental ideas along with applying Dynamic Programming to String algorithms so that you are able to solve all string-based problems. Some of the problems we have covered are: - Check substring: This is an important fundamental problem where we learn how strings can be handled just like numeric data and algorithms for numeric data can be leveraged.Some of the core concepts we explored are string hashing, rolling hash and much more.- Longest common substring: This is a core problem as this uses the concepts we gained in the previous problems and an alternative solution is to use Dynamic Programming.The core idea is to apply Dynamic Programming over two different string data.- Longest repeating substring: In line with our previous problem, we explored how to apply Dynamic Programming for this problem. The key distinction is that we are dealing with just 1 string instead of 2 strings as in the previous problem. Unlike the previous problem, the Dynamic Programming approach is the only optimal solution.With these problems and the thought process to solve them, you will be fully prepared.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from professors at The University of Tokyo and Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.Books in this series ("Day before coding Interview"): - Problems for the day before your coding interview- Greedy Algorithms for the day before your Coding Interview- Dynamic Programming for the day before your coding interview- String Algorithms for the day before your Coding Interview
Author: Harry He
Publisher: Apress
ISBN: 1430247622
Category : Computers
Languages : en
Pages : 292
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Book Description
This book is about coding interview questions from software and Internet companies. It covers five key factors which determine performance of candidates: (1) the basics of programming languages, data structures and algorithms, (2) approaches to writing code with high quality, (3) tips to solve difficult problems, (4) methods to optimize code, (5) soft skills required in interviews. The basics of languages, algorithms and data structures are discussed as well as questions that explore how to write robust solutions after breaking down problems into manageable pieces. It also includes examples to focus on modeling and creative problem solving. Interview questions from the most popular companies in the IT industry are taken as examples to illustrate the five factors above. Besides solutions, it contains detailed analysis, how interviewers evaluate solutions, as well as why they like or dislike them. The author makes clever use of the fact that interviewees will have limited time to program meaningful solutions which in turn, limits the options an interviewer has. So the author covers those bases. Readers will improve their interview performance after reading this book. It will be beneficial for them even after they get offers, because its topics, such as approaches to analyzing difficult problems, writing robust code and optimizing, are all essential for high-performing coders.
Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
Greedy algorithms are fundamentally important as it encapsulate algorithmic problems where choosing the most obvious answer for the current sub-problem results in solving the entire problem.This seems to be easy and it is easy. The difficult part is to understand if a problem can be solved using a Greedy algorithm. There are numerous problems where a greedy algorithm may look to be the solution but is in fact, not the case.In this book, we have covered some greedy problems which you can cover in a day to get prepared just before your coding interview.We have covered problems like:* Finding largest number with given number of digits and sum (Important as it illustrates how an exponential search space can be traversed in linear time)* Number as a sum of Fibonacci terms (Requires deep insights from Number Theory to truly understand this problem which we explained)* Maximal clique (a perfect problem as it shows greedy algorithms can be effectively used in finding structures within graphs)* Task Selection (this problem is unique as slightly changing the problem statement, no greedy approach will be valid. In fact, this is a problem where Greedy Algorithm is preferred over a corresponding Dynamic Programming approach.)* Graph Coloring (This is a real-world problem and vast amount of research has been put into this. We presented a greedy solution to this along with the general idea of other approaches.)and many more ideas.We have added pseudocode for each approach which you should go through and implement in your programming language of choice to get in the flow of implementing ideas as well.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.
Author: Adnan Aziz
Publisher: EPI
ISBN: 1479274836
Category : Business & Economics
Languages : en
Pages : 530
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Book Description
The core of EPI is a collection of over 300 problems with detailed solutions, including 100 figures, 250 tested programs, and 150 variants. The problems are representative of questions asked at the leading software companies. The book begins with a summary of the nontechnical aspects of interviewing, such as common mistakes, strategies for a great interview, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI. The technical core of EPI is a sequence of chapters on basic and advanced data structures, searching, sorting, broad algorithmic principles, concurrency, and system design. Each chapter consists of a brief review, followed by a broad and thought-provoking series of problems. We include a summary of data structure, algorithm, and problem solving patterns.
Author: Leonardo Rossi
Publisher:
ISBN:
Category :
Languages : en
Pages : 182
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Book Description
Are you preparing for a programming interview? Would you like to work at one of the Internet giants, such as Google, Facebook, Amazon, Apple, Microsoft or Netflix? Are you looking for a software engineer position? Are you studying computer science or programming? Would you like to improve your programming skills? If the answer to any of these questions is yes, this book is for you! The book contains very detailed answers and explanations for the most common dynamic programming problems asked in programming interviews. The solutions consist of cleanly written code, with plenty of comments, accompanied by verbal explanations, hundreds of drawings, diagrams and detailed examples, to help you get a good understanding of even the toughest problems. The goal is for you to learn the patterns and principles needed to solve even dynamic programming problems that you have never seen before. Here is what you will get: A 180-page book presenting dynamic programming problems that are often asked in interviews. Multiple solutions for each problem, starting from simple but naive answers that are gradually improved until reaching the optimal solution. Plenty of detailed examples and walkthroughs, so that you can see right away how the solution works. 350+ drawings and diagrams which cater towards visual learners. Clear and detailed verbal explanations of how to approach the problems and how the code works. Analysis of time and space complexity. Discussion of other variants of the same problem, with solutions. Unit tests, including the reasoning behind choosing each one (edge case identification, performance evaluation etc.). Suggestions regarding what clarification questions you should ask, for each problem. Multiple solutions to the problems, where appropriate. General Python implementation tips. Wishing you the best of luck with your interviews!
