Machine Learning End To End Guide For Java Developers
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Machine Learning End To End Guide For Java Developers
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Author : Richard M. Reese
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-10-05
Machine Learning End To End Guide For Java Developers written by Richard M. Reese and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-05 with Computers categories.
Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical use-cases Who This Book Is For This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. What You Will Learn Understand key data analysis techniques centered around machine learning Implement Java APIs and various techniques such as classification, clustering, anomaly detection, and more Master key Java machine learning libraries, their functionality, and various kinds of problems that can be addressed using each of them Apply machine learning to real-world data for fraud detection, recommendation engines, text classification, and human activity recognition Experiment with semi-supervised learning and stream-based data mining, building high-performing and real-time predictive models Develop intelligent systems centered around various domains such as security, Internet of Things, social networking, and more In Detail Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. The next couple of sections cover applying machine learning methods using Java to a variety of chores including classifying, predicting, forecasting, market basket analysis, clustering stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, and deep learning. The last section highlights real-world test cases such as performing activity recognition, developing image recognition, text classification, and anomaly detection. The course includes premium content from three of our most popular books: Java for Data Science Machine Learning in Java Mastering Java Machine Learning On completion of this course, you will understand various machine learning techniques, different machine learning java algorithms you can use to gain data insights, building data models to analyze larger complex data sets, and incubating applications using Java and machine learning algorithms in the field of artificial intelligence. Style and approach This comprehensive course proceeds from being a tutorial to a practical guide, providing an introduction to machine learning and different machine learning techniques, exploring machine learning with Java libraries, and demonstrating real-world machine learning use cases using the Java platform.
Machine Learning End To End Guide For Java Developers
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Author : Richard M. Reese
language : en
Publisher:
Release Date : 2017-10-05
Machine Learning End To End Guide For Java Developers written by Richard M. Reese and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-05 with categories.
Develop, Implement and Tuneup your Machine Learning applications using the power of Java programmingAbout This Book* Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects* Address predictive modeling problems using the most popular machine learning Java libraries* A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical use-casesWho This Book Is ForThis course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have.What You Will Learn* Understand key data analysis techniques centered around machine learning* Implement Java APIs and various techniques such as classification, clustering, anomaly detection, and more* Master key Java machine learning libraries, their functionality, and various kinds of problems that can be addressed using each of them* Apply machine learning to real-world data for fraud detection, recommendation engines, text classification, and human activity recognition* Experiment with semi-supervised learning and stream-based data mining, building high-performing and real-time predictive models* Develop intelligent systems centered around various domains such as security, Internet of Things, social networking, and moreIn DetailMachine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. The next couple of sections cover applying machine learning methods using Java to a variety of chores including classifying, predicting, forecasting, market basket analysis, clustering stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, and deep learning.The last section highlights real-world test cases such as performing activity recognition, developing image recognition, text classification, and anomaly detection. The course includes premium content from three of our most popular books:* Java for Data Science* Machine Learning in Java* Mastering Java Machine LearningOn completion of this course, you will understand various machine learning techniques, different machine learning java algorithms you can use to gain data insights, building data models to analyze larger complex data sets, and incubating applications using Java and machine learning algorithms in the field of artificial intelligence.Style and approachThis comprehensive course proceeds from being a tutorial to a practical guide, providing an introduction to machine learning and different machine learning techniques, exploring machine learning with Java libraries, and demonstrating real-world machine learning use cases using the Java platform.
Knowledge Management And Digital Transformation Power
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Author : Orhan TORKUL
language : en
Publisher: Efe Akademi Yayınları
Release Date : 2022-11-25
Knowledge Management And Digital Transformation Power written by Orhan TORKUL and has been published by Efe Akademi Yayınları this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-25 with Computers categories.
İÇİNDEKİLER ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNIQUES IN DISTANCE EDUCATION (2012-2021): A SYSTEMATIC REVIEW MEHMET BARIŞ HORZUM - DENİZ DEMİRCİOĞLU DİREN THE ROLE OF CUSTOMER KNOWLEDGE IN DIGITAL TRANSFORMATION: CUSTOMER KNOWLEDGE MANAGEMENT AS A COMPETITIVE ADVANTAGE THROUGH SOCIAL MEDIA PLATFORMS LEVENT ÇALLI MACHINE LEARNING AS A TOOL FOR ACHIEVING DIGITAL TRANSFORMATION MERVE ŞİŞCİ - YUNUS EMRE TORKUL - İHSAN HAKAN SELVİ BLOCKCHAIN-BASED ENERGY MANAGEMENT FOR SUPPLY CHAIN MANAGEMENT ERAY AÇIKGÖZ - BERRİN DENİZHAN A STUDY ON DEEP LEARNING BASED APPLICATIONS USED IN AGRICULTURE IN TURKIYE GÜNAY TEMÜR BLOCKCHAIN AND INFORMATION SHARING FATİH ÇALLI INDUSTRY 4.0, SMART FACTORIES AND EFFECTS ON BUSINESS TİJEN ÖVER ÖZÇELİK - İHSAN HAKAN SELVİ - AYTEN YILMAZ YALÇINER - MUHAMMED TAHA ZEREN ANALYSIS OF THE PARAMETERS THAT AFFECT THE MOISTURE CONTENT OF THE PUMPKIN BY DATA MINING FEYZA GÜRBÜZ OPPORTUNITIES AND CHALLENGES OF DIGITAL TRANSFORMATION IN SMEs-THE ROLE OF DYNAMIC CAPABILITIES AS A CATALYST BÜŞRA ALMA ÇALLI A CUSTOMER-CENTRIC ANALYTICS FRAMEWORK AND INSIGHTS OF DIGITAL TRANSFORMATION ÖMER FARUK SEYMEN THE FUTURE OF MONEY AS A FINANCIAL INVESTMENT TOOL: CENTRAL BANK DIGITAL CURRENCY İNCİ MERVE ALTAN
Transformers For Machine Learning
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Author : Uday Kamath
language : en
Publisher: CRC Press
Release Date : 2022-05-24
Transformers For Machine Learning written by Uday Kamath and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-24 with Computers categories.
Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers. Key Features: A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in Google Colab. The theoretical explanations of the state-of-the-art transformer architectures will appeal to postgraduate students and researchers (academic and industry) as it will provide a single entry point with deep discussions of a quickly moving field. The practical hands-on case studies and code will appeal to undergraduate students, practitioners, and professionals as it allows for quick experimentation and lowers the barrier to entry into the field.
The Definitive Guide To Modern Java Clients With Javafx
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Author : Stephen Chin
language : en
Publisher: Springer Nature
Release Date : 2024-12-05
The Definitive Guide To Modern Java Clients With Javafx written by Stephen Chin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-05 with Computers categories.
Build enhanced visual experiences and design and deploy modern, easy-to-maintain, client applications across a variety of platforms. This book will show you how these applications can take advantage of JavaFX’s latest user interface components, 3D technology, and cloud services to create immersive visualizations and allow high-value data manipulation. This book is a professional reference for building Java applications for desktop, mobile, and embedded in the Cloud age. It offers end-to-end coverage of the latest features in JavaFX 21 and 23. This third edition has been updated to include new features introduced in JavaFX 21 and 23, including NEW APIs: Map, FlatMap, and OrElse fluent bindings for ObservableValue, along with the new Subscription API. Additionally, it's updated to account for new bug fixes and overall improvements to existing functionality in Java. After reading this book, you will be equipped to upgrade legacy client applications, develop cross-platform applications in Java, and build enhanced desktop and mobile native clients. What You Will Learn Create modern client applications in Java using the latest JavaFX 21 and 23 Build enterprise clients that will enable integration with existing cloud services Use advanced visualization and 3D features Deploy on desktop, mobile, and embedded devices Who This Book Is For Professional Java developers who are interested in learning the latest client Java development techniques to fill out their skills set
Machine Learning With Apache Spark Quick Start Guide
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Author : Jillur Quddus
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-26
Machine Learning With Apache Spark Quick Start Guide written by Jillur Quddus and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-26 with Computers categories.
Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key FeaturesMake a hands-on start in the fields of Big Data, Distributed Technologies and Machine LearningLearn how to design, develop and interpret the results of common Machine Learning algorithmsUncover hidden patterns in your data in order to derive real actionable insights and business valueBook Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learnUnderstand how Spark fits in the context of the big data ecosystemUnderstand how to deploy and configure a local development environment using Apache SparkUnderstand how to design supervised and unsupervised learning modelsBuild models to perform NLP, deep learning, and cognitive services using Spark ML librariesDesign real-time machine learning pipelines in Apache SparkBecome familiar with advanced techniques for processing a large volume of data by applying machine learning algorithmsWho this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.
Software Development Lifecycle Made Simple A Practical Guide With Examples
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Author : William E. Clark
language : en
Publisher: Walzone Press
Release Date : 2025-04-22
Software Development Lifecycle Made Simple A Practical Guide With Examples written by William E. Clark and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-22 with Computers categories.
Software Development Lifecycle Made Simple: A Practical Guide with Examples offers a clear and comprehensive introduction to the processes, principles, and best practices of modern software development. Designed for beginners and aspiring professionals, this book demystifies the complexities of the software development lifecycle (SDLC), guiding readers step by step from foundational programming concepts to the structured methodologies that drive successful projects. The book is organized to mirror real-world workflows, covering every phase of development including planning, requirements analysis, design, implementation, testing, deployment, and ongoing maintenance. Each chapter breaks down essential topics such as algorithms, programming languages, debugging, version control, collaborative practices, quality assurance, security, and project management. A continuous case study reinforces each concept by demonstrating how it applies to a practical software project, making the principles tangible and directly relevant to actual development scenarios. Readers will gain a strong understanding of how software products are envisioned, constructed, and maintained in professional settings. By emphasizing both technical skills and the broader project context, this guide equips learners with the knowledge and confidence needed to participate effectively in software development teams. Whether preparing for a technical role or seeking to understand the mechanics of software project execution, this book provides a reliable foundation and a practical pathway for further growth in the field.
Aws Certified Big Data Specialty Bds C01
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date :
Aws Certified Big Data Specialty Bds C01 written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Study Aids categories.
Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Fusion Of Web Development A Comprehensive Guide To Modern Web Technologies
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-12
Fusion Of Web Development A Comprehensive Guide To Modern Web Technologies written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-12 with Technology & Engineering categories.
In a rapidly evolving digital landscape, the mastery of modern web development technologies has become a necessity for creating engaging and effective online experiences. Fusion of Web Development: A Comprehensive Guide to Modern Web Technologies serves as your ultimate resource, meticulously crafted to equip you with the knowledge and skills required to navigate the complexities of contemporary web development. Embark on a comprehensive journey through the intricate world of HTML5, CSS3, JavaScript, and their seamless integration with robust back-end technologies. Delve into the depths of front-end frameworks and full-stack development, uncovering the secrets of building sophisticated web applications that captivate users and deliver exceptional performance. With this guide in hand, you will unravel the mysteries of HTML5, gaining a profound understanding of its structural elements, multimedia capabilities, and interactive forms. Transform your web pages into visually stunning and functionally rich masterpieces by harnessing the power of CSS3's advanced features, exploring layout techniques, animations, and color theory. Unleash the dynamic potential of JavaScript, unlocking the secrets of interactivity and responsiveness. Master event-driven programming, asynchronous techniques, and debugging methodologies to create web applications that engage users and provide seamless experiences. Discover the benefits of front-end frameworks, comparing popular options and delving into the concepts of component-based architecture and single-page applications. Learn how to select the most appropriate framework for your specific project, ensuring scalability, maintainability, and cutting-edge performance. Venture into the realm of back-end technologies, exploring the intricacies of server-side programming languages, database management systems, and the art of crafting dynamic websites. Secure your web applications with robust authentication and authorization mechanisms, ensuring the privacy and integrity of user data. Optimize performance for lightning-fast responsiveness, delivering a seamless user experience across devices and platforms. As you delve into the intricacies of full-stack development, uncover the synergy between front-end and back-end components, mastering the skills necessary to create cohesive and powerful web applications. Understand the role of full-stack developers and the challenges they encounter, gaining the expertise to seamlessly integrate front-end aesthetics with back-end functionality. Finally, explore the essential aspects of web deployment, including selecting a reliable web hosting provider, configuring servers, and uploading website files. Learn the intricacies of domain name management and website maintenance, ensuring your web presence remains secure, accessible, and optimized for maximum performance. If you like this book, write a review on google books!
The Definitive Guide To Machine Learning Operations In Aws
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Author : Neel Sendas
language : en
Publisher: Springer Nature
Release Date : 2025-01-03
The Definitive Guide To Machine Learning Operations In Aws written by Neel Sendas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Foreword by Dr. Shreyas Subramanian, Principal Data Scientist, Amazon This book focuses on deploying, testing, monitoring, and automating ML systems in production. It covers AWS MLOps tools like Amazon SageMaker, Data Wrangler, and AWS Feature Store, along with best practices for operating ML systems on AWS. This book explains how to design, develop, and deploy ML workloads at scale using AWS cloud's well-architected pillars. It starts with an introduction to AWS services and MLOps tools, setting up the MLOps environment. It covers operational excellence, including CI/CD pipelines and Infrastructure as code. Security in MLOps, data privacy, IAM, and reliability with automated testing are discussed. Performance efficiency and cost optimization, like Right-sizing ML resources, are explored. The book concludes with MLOps best practices, MLOPS for GenAI, emerging trends, and future developments in MLOps By the end, readers will learn operating ML workloads on the AWS cloud. This book suits software developers, ML engineers, DevOps engineers, architects, and team leaders aspiring to be MLOps professionals on AWS. What you will learn: ● Create repeatable training workflows to accelerate model development ● Catalog ML artifacts centrally for model reproducibility and governance ● Integrate ML workflows with CI/CD pipelines for faster time to production ● Continuously monitor data and models in production to maintain quality ● Optimize model deployment for performance and cost Who this book is for: This book suits ML engineers, DevOps engineers, software developers, architects, and team leaders aspiring to be MLOps professionals on AWS.