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This book is designed to equip the reader with all of the best followed, efficient, well-structured program logics in the form of flowcharts and algorithms. The basic purpose of flowcharting is to create the sequence of steps for showing the solution to problems through arithmetic and/or logical manipulations used to instruct computers. The applied and illustrative examples from different subject areas will definitely encourage readers to learn the logic leading to solid programming basics. Features: Uses flowcharts and algorithms to solve problems from everyday applications, teaching the logic needed for the creation of computer instructions Covers arrays, looping, file processing, etc.
This document has been prepared for students who are designing program for any language.
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
Master machine learning techniques with R to deliver insights for complex projects About This Book Get to grips with the application of Machine Learning methods using an extensive set of R packages Understand the benefits and potential pitfalls of using machine learning methods Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful. What You Will Learn Gain deep insights to learn the applications of machine learning tools to the industry Manipulate data in R efficiently to prepare it for analysis Master the skill of recognizing techniques for effective visualization of data Understand why and how to create test and training data sets for analysis Familiarize yourself with fundamental learning methods such as linear and logistic regression Comprehend advanced learning methods such as support vector machines Realize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages. Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.
DESCRIPTIONThis book is specially designed to serve as the textbook for the students of various streams such as PGDCA, B.Tech. /B.E., BCA, BSc M.Tech. /M.E., MCA, MS and cover all the topics of Data Structure. The subject data structure is of prime importance for the students of Computer Science and IT. It is the practical approach to understanding the basics and concepts of the data structure. All the concepts are implemented in C language in an easy manner. To make clarity on the topic, diagrams, examples, and programs are given throughout the book. KEY FEATURESThis book is specially designed for beginners, explains all basics and concepts about data structure. The source code of all data structures is given in C language.Important data structures like Stack, Queue, Linked List, Tree, and Graph are well explained.Solved example, frequently asked in the examinations are given which will serve as a useful reference source. Effective description of sorting algorithm (Quick Sort, Heap Sort, Merge Sort etc.)CD contains all programming codes in 'C'.CONTENTS Algorithm and Flow ChartsAlgorithm AnalysisData structureFunctions and RecursionArrays and PointersStringStacksQueuesLinked ListsTreesGraphsHashing and Sorting CD Contains all Programming codes in 'C'
Explore Golang's data structures and algorithms to design, implement, and analyze code in the professional setting Key FeaturesLearn the basics of data structures and algorithms and implement them efficientlyUse data structures such as arrays, stacks, trees, lists and graphs in real-world scenariosCompare the complexity of different algorithms and data structures for improved code performanceBook Description Golang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications. Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving. The book begins with an introduction to Go data structures and algorithms. You'll learn how to store data using linked lists, arrays, stacks, and queues. Moving ahead, you'll discover how to implement sorting and searching algorithms, followed by binary search trees. This book will also help you improve the performance of your applications by stringing data types and implementing hash structures in algorithm design. Finally, you'll be able to apply traditional data structures to solve real-world problems. By the end of the book, you'll have become adept at implementing classic data structures and algorithms in Go, propelling you to become a confident Go programmer. What you will learnImprove application performance using the most suitable data structure and algorithmExplore the wide range of classic algorithms such as recursion and hashing algorithmsWork with algorithms such as garbage collection for efficient memory management Analyze the cost and benefit trade-off to identify algorithms and data structures for problem solvingExplore techniques for writing pseudocode algorithm and ace whiteboard coding in interviewsDiscover the pitfalls in selecting data structures and algorithms by predicting their speed and efficiencyWho this book is for This book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage.
If you know basic high-school math, you can quickly learn and apply the core concepts of computer science with this concise, hands-on book. Led by a team of experts, you’ll quickly understand the difference between computer science and computer programming, and you’ll learn how algorithms help you solve computing problems. Each chapter builds on material introduced earlier in the book, so you can master one core building block before moving on to the next. You’ll explore fundamental topics such as loops, arrays, objects, and classes, using the easy-to-learn Ruby programming language. Then you’ll put everything together in the last chapter by programming a simple game of tic-tac-toe. Learn how to write algorithms to solve real-world problems Understand the basics of computer architecture Examine the basic tools of a programming language Explore sequential, conditional, and loop programming structures Understand how the array data structure organizes storage Use searching techniques and comparison-based sorting algorithms Learn about objects, including how to build your own Discover how objects can be created from other objects Manipulate files and use their data in your software
This is a condensed version of Chapter III (Algorithms & Programming Languages) from the book "Fundamentals of Modern Information Technology" (Italian Edition). This book has been written primarily for students, but also for the professional, and it can serve as a starting point for anyone who is beginning the study of computer science and information systems for the first time. In the following text, algorithms and flowcharts are analyzed accurately, with clear examples, and with the implementation in C code, both elementary and complex algorithms are studied. Data types (simple and structured) are initially introduced, and algorithms and flowcharts are defined and illustrated with graphical and textual explanations. In the next sections, simple and complex standard algorithms with their flowcharts are studied: everything is integrated with explanations and tables to have a step by step evolution of the algorithms. The main analyzed algorithms are: the sum of three or n numbers in a loop, the maximum and minimum search, the linear/sequential search, the binary search, the bubble sort, the selection sort, the merging of two sorted arrays, and the reading chars from file algorithm. The last section of the text is devoted to the introduction of the C language and the implementation of the code, which is connected to the studied algorithms.
Algorithms serve an important purpose in the field of psychopharmacology as heuristics for avoiding the biases and cognitive lapses that are common when prescribing for many conditions whose treatment is based on complex data. Unique in the field, this title compiles twelve papers from the Psychopharmacology Algorithm Project at the Harvard South Shore Psychiatry Residency Training Program and presents practical ways to adopt evidence-based practices into the day-to-day treatment of patients. Psychopharmacology Algorithms is a useful resource for practicing psychiatrists, residents, and fellows, as well as psychiatric nurse practitioners, psychiatric physician assistants who prescribe, advanced practice pharmacists who prescribe, and primary care clinicians. Teachers of psychopharmacology may find it particularly valuable. Researchers in clinical psychopharmacology may find it helpful in identifying important practice areas that are in need of further study.