Download or read book Dynamic Programming for Coding Interviews written by Meenakshi and published by Notion Press. This book was released on 2017-01-18 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Think Like a Programmer written by V. Anton Spraul and published by No Starch Press. This book was released on 2012-08-12 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The real challenge of programming isn't learning a language's syntax—it's learning to creatively solve problems so you can build something great. In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to: –Split problems into discrete components to make them easier to solve –Make the most of code reuse with functions, classes, and libraries –Pick the perfect data structure for a particular job –Master more advanced programming tools like recursion and dynamic memory –Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.
Download or read book Programming Interview Problems written by Leonardo Rossi and published by . This book was released on 2020-11-05 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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!
Download or read book Dynamic Programming for the Day Before Your Coding Interview written by Ue Kiao and published by . This book was released on 2020-04-28 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Dynamic Programming for Coding Interviews written by Meenakshi Rawat and published by Independently Published. This book was released on 2023-03-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: On a computer, where the non-recursive Dynamic Programming solution to compute the n'th Fibonacci term takes 1 second to find the 40th term, the corresponding recursive solution will take approximately 56 hours to find the same 40th Fibonacci term. It is because the small innocent-looking recursive solution of Fibonacci takes exponential time, whereas the DP solution takes linear time. Dynamic programming questions are the most difficult to answer in competitions and interviews. In most coding competitions, a recursive solution will not pass all test cases. This book takes dynamic programming head-on.
Download or read book Dynamic Programming written by A. Kaufmann and published by Academic Press. This book was released on 2011-10-14 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work discusses the value of dynamic programming as a method of optimization for the sequential phenomena encountered in economic studies or in advanced technological programs such as those associated with space flights. The dynamic programs which are considered are defined for a deterministic universe, or one with probabilities; both categories are of equal importance in the practice of operations research or of scientific management.
Download or read book Dynamic Programming written by Richard Bellman and published by Courier Corporation. This book was released on 2013-04-09 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to mathematical theory of multistage decision processes takes a "functional equation" approach. Topics include existence and uniqueness theorems, optimal inventory equation, bottleneck problems, multistage games, Markovian decision processes, and more. 1957 edition.
Download or read book Reinforcement Learning and Dynamic Programming Using Function Approximators written by Lucian Busoniu and published by CRC Press. This book was released on 2017-07-28 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.
Download or read book Dynamic Programming written by Richard Bellman and published by . This book was released on 1957 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Learn to Code by Solving Problems written by Daniel Zingaro and published by No Starch Press. This book was released on 2021-06-29 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to Code by Solving Problems is a practical introduction to programming using Python. It uses coding-competition challenges to teach you the mechanics of coding and how to think like a savvy programmer. Computers are capable of solving almost any problem when given the right instructions. That’s where programming comes in. This beginner’s book will have you writing Python programs right away. You’ll solve interesting problems drawn from real coding competitions and build your programming skills as you go. Every chapter presents problems from coding challenge websites, where online judges test your solutions and provide targeted feedback. As you practice using core Python features, functions, and techniques, you’ll develop a clear understanding of data structures, algorithms, and other programming basics. Bonus exercises invite you to explore new concepts on your own, and multiple-choice questions encourage you to think about how each piece of code works. You’ll learn how to: Run Python code, work with strings, and use variables Write programs that make decisions Make code more efficient with while and for loops Use Python sets, lists, and dictionaries to organize, sort, and search data Design programs using functions and top-down design Create complete-search algorithms and use Big O notation to design more efficient code By the end of the book, you’ll not only be proficient in Python, but you’ll also understand how to think through problems and tackle them with code. Programming languages come and go, but this book gives you the lasting foundation you need to start thinking like a programmer.
Download or read book Dynamic Economics written by Jerome Adda and published by MIT Press. This book was released on 2023-05-09 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers. This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics. In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation. The original contribution of Dynamic Economics: Quantitative Methods and Applications lies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation.
Download or read book Applied Dynamic Programming written by Richard E. Bellman and published by Princeton University Press. This book was released on 2015-12-08 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive study of dynamic programming applied to numerical solution of optimization problems. It will interest aerodynamic, control, and industrial engineers, numerical analysts, and computer specialists, applied mathematicians, economists, and operations and systems analysts. Originally published in 1962. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Download or read book Cracking the Coding Interview written by Gayle Laakmann McDowell and published by CreateSpace. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Algorithmic Thinking written by Daniel Zingaro and published by No Starch Press. This book was released on 2020-12-15 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, problem-based introduction to building algorithms and data structures to solve problems with a computer. Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems. Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like: The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations The union-find data structure to answer questions about connections in a social network or determine who are friends or enemies The heap data structure to determine the amount of money given away in a promotion The hash-table data structure to determine whether snowflakes are unique or identify compound words in a dictionary NOTE: Each problem in this book is available on a programming-judge website. You'll find the site's URL and problem ID in the description. What's better than a free correctness check?
Download or read book Introduction to Dynamic Programming written by George L. Nemhauser and published by . This book was released on 1966 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book 7 days with Dynamic Programming written by Aditya Chatterjee and published by OpenGenus. This book was released on 2020-08-24 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Learning and Approximate Dynamic Programming written by Jennie Si and published by John Wiley & Sons. This book was released on 2004-08-02 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete resource to Approximate Dynamic Programming (ADP), including on-line simulation code Provides a tutorial that readers can use to start implementing the learning algorithms provided in the book Includes ideas, directions, and recent results on current research issues and addresses applications where ADP has been successfully implemented The contributors are leading researchers in the field