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Mathematical Dynamic Programming

Om Mathematical Dynamic Programming

This book will change your Algorithmic Problem-Solving skills forever. Read it now to level up your future. This book "Mathematical Dynamic Programming" is the only book you need to master Dynamic Programming. The focus is towards core Mathematical problems for Coding Interviews. Many fail to solve basic DP problems such as Longest Increasing Subsequence and Shortest Common SuperSequence. All such problems are covered in this book in depth. This book has covered 24 most important DP problems with detailed explanation along with sample implementations. You should go through the implementations irrespective of the Programming Language you use as the ideas remain the same. Improving Implementation skills is important for Coding Interviews and this book will help you achieve it. If you have time, you should read one chapter every day and think about the problem on your own. Try to find different variants. These carefully selected problems will help you level up your skills and help secure a good job or internship soon. Get started with this book and change the equation of your career. Book: Mathematical Dynamic Programming Authors (3): Aditya Chatterjee, Ue Kiao, Geoffrey Ziskovin About the authors: Aditya Chatterjee is an Independent Researcher, Technical Author and the Founding Member of OPENGENUS, a scientific community focused on Computing Technology. Ue Kiao is a Japanese Software Developer and has played key role in designing systems like TaoBao, AliPay and many more. She has completed her B. Sc in Mathematics and Computing Science at National Taiwan University and PhD at Tokyo Institute of Technology. Geoffrey Ziskovin is an American Software Engineer with an experience of over 30 years. He has interviewed over 700 candidates worldwide for various Fortune 500 companies. Published: May 2022 (Edition 1) Publisher: (c) OpenGenus

Visa mer
  • Språk:
  • Engelska
  • ISBN:
  • 9798831194098
  • Format:
  • Häftad
  • Sidor:
  • 178
  • Utgiven:
  • 21. maj 2022
  • Mått:
  • 152x229x10 mm.
  • Vikt:
  • 245 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 17. december 2024

Beskrivning av Mathematical Dynamic Programming

This book will change your Algorithmic Problem-Solving skills forever. Read it now to level up your future. This book "Mathematical Dynamic Programming" is the only book you need to master Dynamic Programming. The focus is towards core Mathematical problems for Coding Interviews. Many fail to solve basic DP problems such as Longest Increasing Subsequence and Shortest Common SuperSequence. All such problems are covered in this book in depth. This book has covered 24 most important DP problems with detailed explanation along with sample implementations.
You should go through the implementations irrespective of the Programming Language you use as the ideas remain the same. Improving Implementation skills is important for Coding Interviews and this book will help you achieve it. If you have time, you should read one chapter every day and think about the problem on your own. Try to find different variants.
These carefully selected problems will help you level up your skills and help secure a good job or internship soon. Get started with this book and change the equation of your career.
Book: Mathematical Dynamic Programming
Authors (3): Aditya Chatterjee, Ue Kiao, Geoffrey Ziskovin About the authors:
Aditya Chatterjee is an Independent Researcher, Technical Author and the Founding Member of OPENGENUS, a scientific community focused on Computing Technology.
Ue Kiao is a Japanese Software Developer and has played key role in designing systems like TaoBao, AliPay and many more. She has completed her B. Sc in Mathematics and Computing Science at National Taiwan University and PhD at Tokyo Institute of Technology.
Geoffrey Ziskovin is an American Software Engineer with an experience of over 30 years. He has interviewed over 700 candidates worldwide for various Fortune 500 companies.
Published: May 2022 (Edition 1)
Publisher: (c) OpenGenus

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