Search results for "Data Structures and Algorithms in Java"
Items we need to order for you
Essential Data Structures and Algorithms in Java
Master essential data structures and algorithms in Java with clear examples, visual walkthroughs, and real-world coding exercises designed to build your problem-solving skills fastKey FeaturesBuild solid foundations with a complete overview of core DSA conceptsImplement advanced data structures for AI agents and complex systemsMaster Java Collections and complexity analysis for scalable applicationsVisualize and debug algorithms with detailed annotated walkthroughsBook DescriptionDeveloping efficient, reliable software starts with mastering data structures and algorithms. This practical guide helps you bridge theory and practice using Java, focusing on real-world challenges and pragmatic solutions. You will explore foundational data structures such as arrays, lists, stacks, queues, trees, and graphs, and learn how to implement them natively and leverage the Java Collections Framework to build scalable applications. With each concept, you will work through step-by-step exercises that illustrate how algorithms are applied to tasks such as searching, sorting, and traversing data.Rather than being theory-heavy or overly abstract, this book takes a problem-first approach, balancing conceptual explanations with immediate hands-on application. Visual walkthroughs, annotated code, and progressive exercises guide you through each concept, helping you internalize how different structures and algorithms impact performance. Each chapter ends with review problems and thought exercises designed to reinforce key ideas and build your confidence through practice.Guided by a veteran software engineer with over 20 years of industry experience, you will gain the skills to implement advanced data structures for modern software systems and write faster, cleaner, and more effective Java code in real development environments.What you will learnUnderstand and implement core data structures in JavaAnalyze time and space complexity with Big O notationSolve coding problems with arrays, linked lists, and hash mapsUse stacks and queues to manage linear data workflowsApply tree and graph algorithms to hierarchical and networked dataMaster dynamic programming approachesDesign concurrent applications using Java's built-in toolsEvaluate algorithmic trade-offs for real-world applications including AIWho this book is forPerfect for aspiring Java developers, CS students, and software engineers with a foundation in JDK 11+ and OOP looking for a practical DSA refresher. This book skips basic syntax tutorials to front-load core principles, allowing you to turn theory into high-performance logic. Master complex algorithms and apply proven problem-solving patterns to write faster, cleaner, and AI-native Java code.
R 1,628.00
Data Structures and Algorithms Using C#
C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for C# implementation of data structures and algorithms found in the .NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O notation to analyze the efficiency of an approach. Coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. This is the perfect resource for C# professionals and students alike.
R 2,979.47
Data Structures and Algorithms Using C#
C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for C# implementation of data structures and algorithms found in the .NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O notation to analyze the efficiency of an approach. Coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. This is the perfect resource for C# professionals and students alike.
R 5,694.38
R 1,644.13
R 1,343.00
Data Structures and Algorithms Using Visual Basic.NET
This is the first Visual Basic.NET book to provide a comprehensive discussion of the major data structures and algorithms. Here, instead of having to translate material on C++ or Java, the professional or student VB.NET programmer will find a tutorial on how to use data structures and algorithms and a reference for implementation using VB.NET for data structures and algorithms from the .NET Framework Class Library as well as those which must be developed by the programmer. In an object-oriented fashion, the author presents arrays and arraylists, linked lists, hash tables, dictionaries, trees, graphs, sorting and searching as well as more advanced algorithms, such as probabilistic algorithms and dynamic programming. His approach is very practical, for example using timing tests rather than Big O analysis to compare the performance of data structures and algorithms. This book can be used in both beginning and advanced computer programming courses that use the VB.NET language and, most importantly, by the professional VB programmer.
R 3,038.25
R 428.00
R 611.00
Hands-On Data Structures and Algorithms with Python
Learn to implement complex data structures and algorithms using PythonKey FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook DescriptionData structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is forThis book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
R 1,498.00
Java Concurrency and Parallelism
Unlock Java's full potential for cloud computing through expert insights from real-world case studies and stay ahead with the latest trends in agile and robust Java application developmentKey FeaturesMaster concurrency and parallelism to overcome cloud computing challenges in JavaBuild scalable solutions with Big Data, ML, microservices, and serverless architecturesExplore cloud scaling, GPU utilization, and future tech innovations in Java applicationsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIf you’re a software developer, architect, or systems engineer, exploring Java’s concurrency utilities and synchronization in the cloud, this book is an essential resource. Tech visionary Jay Wang, with over three decades of experience transforming industry giants, brings unparalleled expertise to guide you through Java’s concurrency and parallel processing in cloud computing.This comprehensive book starts by establishing the foundational concepts of concurrency and parallelism, vital for cloud-native development, and gives you a complete overview, highlighting challenges and best practices. Wang expertly demonstrates Java’s role in big data, machine learning, microservices, and serverless computing, shedding light on how Java’s tools are effectively utilized in these domains. Complete with practical examples and insights, this book bridges theory with real-world applications, ensuring a holistic understanding of Java in cloud-based scenarios. You’ll navigate advanced topics, such as synchronizing Java’s concurrency with cloud auto-scaling and GPU computing, and be equipped with the skills and foresight to tackle upcoming trends in cloud technology.This book serves as your roadmap to innovation and excellence in Java cloud applications, giving you in-depth knowledge and hands-on practice for mastering Java in the cloud era.What you will learnUnderstand Java concurrency in cloud app developmentGet to grips with the core concepts of serverless computing in JavaBoost cloud scaling and performance using Java skillsImplement Java GPU acceleration for advanced computing tasksGain insights into Java's role in the evolving cloud and AI technologyAccess hands-on exercises for real-world Java applicationsExplore diverse Java case studies in tech and fintechImplement Java in AI-driven cloud and data workflowsAnalyze Java's application in IoT and real-time analyticsWho this book is forThis book is for Java developers, software engineers, and cloud architects with intermediate Java knowledge. It's ideal for professionals transitioning to cloud-native development or seeking to enhance their concurrent programming skills. DevOps engineers and tech leads involved in cloud migration will also find valuable insights. Basic Java proficiency, familiarity with cloud concepts, and some experience with distributed systems is expected.
R 1,433.00
R 1,010.00
R 1,010.00
R 857.41
Mastering Algorithms with Python
Gain a solid understanding of algorithms and improve your problem-solving abilities using Python code. With practical examples and clear explanations, this book bridges the gap between dense academic texts and overly simple industry guides. Focusing on the logic behind essential algorithms such as Breadth First Search (BFS), Depth First Search (DFS), Divide-and-Conquer, Greedy Methods, and Dynamic Programming, the book provides ample examples, from easy to more advanced. By connecting these concepts to real-world examples, such as chess strategies and the Seam Carving, the book helps readers better grasp and apply algorithms. Each chapter also includes fully implemented Python code, making it a practical reference. Mastering Algorithms with Python is ideal for IT professionals looking to enhance their skills and approach algorithms with clarity and confidence. What You Will Learn - - - - Who This Book Is For Software developers, data scientists, machine learning professionals and any curious learners about computer algorithms.
R 912.00
R 1,010.00
Introducing Algorithms in C
Study elementary and complex algorithms with clear examples and implementations in C. This book introduces data types (simple and structured) and algorithms with graphical and textual explanations. In the next sections, you’ll cover simple and complex standard algorithms with their flowcharts: everything is integrated with explanations and tables to give a step-by-step evolution of the algorithms. The main algorithms are: the sum of three or n numbers in a loop, decimal-to-binary conversion, maximum and minimum search, linear/sequential search, binary search, bubble sort, selection sort, merging of two sorted arrays, reading characters from a file, stack management, and factorial and Fibonacci sequences. The last section of Introducing Algorithms in C is devoted to the introduction of the C language and the implementation of the code, which is connected to the studied algorithms. The book is full of screenshots and illustrations showing the meaning of the code. What You Will LearnImplement algorithms in C Work with variables, constants, and primitive and structured typesUse arrays, stacks, queues, graphs, trees, hash tables, records, and filesExplore the design of algorithms Solve searching problems, including binary search, sorting, and bubble/selection sortProgram recursive algorithms with factorial functions and Fibonacci sequences Who This Book Is ForPrimarily beginners: it can serve as a starting point for anyone who is beginning the study of computer science and information systems for the first time.
R 1,075.76
Pro Machine Learning Algorithms
Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a practical understanding of all the levers that can be tuned in a model, before implementing the models in Python/R.You will cover all the major algorithms: supervised and unsupervised learning, which include linear/logistic regression; k-means clustering; PCA; recommender system; decision tree; random forest; GBM; and neural networks. You will also be exposed to the latest in deep learning through CNNs, RNNs, and word2vec for text mining. You will be learning not only the algorithms, but also the concepts of feature engineering to maximize the performance of a model. You will see the theory along with case studies, such as sentiment classification, fraud detection, recommender systems, and image recognition, so that you get the best of both theory and practice for the vast majority of the machine learning algorithms used in industry. Along with learning the algorithms, you will also be exposed to running machine-learning models on all the major cloud service providers.You are expected to have minimal knowledge of statistics/software programming and by the end of this book you should be able to work on a machine learning project with confidence. What You Will LearnGet an in-depth understanding of all the major machine learning and deep learning algorithms Fully appreciate the pitfalls to avoid while building modelsImplement machine learning algorithms in the cloud Follow a hands-on approach through case studies for each algorithmGain the tricks of ensemble learning to build more accurate modelsDiscover the basics of programming in R/Python and the Keras framework for deep learningWho This Book Is ForBusiness analysts/ IT professionals who want to transition into data science roles. Data scientists who want to solidify their knowledge in machine learning.
R 1,736.45
R 1,109.74
R 1,069.00
