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Results 2761-2770 of 3601 (Search time: 0.122 seconds).
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  • Sách/Book

  • Java Persistence with NoSQL: Revolutionize your Java apps with NoSQL integration

    • Authors: Otávio Santana (2024)

  • The book is divided into four parts, covering essential NoSQL concepts, Java principles, Jakarta EE integration, and the integration of NoSQL databases into enterprise architectures. Readers will explore NoSQL databases, comparing their strengths and use cases. They will then master Java coding principles and design patterns necessary for effective NoSQL integration. The book also discusses the latest Jakarta EE specifications, enhancing readers' understanding of Jakarta's role in data storage and retrieval. Finally, readers will learn to implement various NoSQL databases into enterprise-grade solutions, ensuring security, high availability, and fault tolerance.
  • Sách/Book

  • Deep learning for finance : creating machine and deep learning models for trading in Python

    • Authors: Sofien Kaabar (2024)

  • "Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analy...
  • Sách/Book

  • Machine learning with python programming: 2023 a beginners guide The Definitive Guide to Mastering Machine Learning in Python and a Problem-Guide Solver to Creating Real-World Intelligent Systems

    • Authors: James Harrison (2024)

  • "Machine Learning With Python Programming : 2023 A Beginners Guide" is the book you've been waiting for. This comprehensive guide takes you on an exciting journey from the basics of Python programming to the depths of neural networks and deep learning. It demystifies the complex world of machine learning, making it accessible and understandable, regardless of your background. James begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you'll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field's most sophisticated and exciting techniques...
  • Sách/Book

  • Python Machine Learning A Step-by-Step Journey with Scikit-Learn and Tensorflow for Beginners

    • Authors: Chloe Annable (2024)

  • This book is crafted with beginners in mind, providing clear, step-by-step instructions and straightforward language, making it an ideal starting point for anyone intrigued by this captivating subject. Python, with its immense capabilities, opens up a world of possibilities, and this guide will set you on the path to harnessing its potential.
  • Tập bài giảng/Lecture

  • Tập bài giảng môn Đầu tư tài chính

    • Authors: Chu Thị Thu Thuỷ (2021)

  • “Đầu tư tài chính” đề cập các vấn đề lý thuyết cơ bản và chuyên sâu về Đầu tư tài chính bao gồm:Các thuật ngữ cơ bản được sử dụng trong đầu tư tài chính như tài sản tài chính, rủi ro, tỷ suất lợi tức và rủi ro của tài sản tài chính.
  • Sách/Book

  • Machine learning for complex and unmanned systems

    • Authors: Esteban Tlelo-Cuautle (2023)

  • "This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The main topics covered under this title include: machine learning, artificial intelligence, cryptography, submarines, drones, security in healthcare, Internet of Things and robotics. This book can be used by graduate students, industrial and academic professionals to revise real case studies in applying machine learning in the areas of modeling, simulation and optimization of complex systems, cryptography, electronics, healthcare, control systems, Internet of Things, security, and unmanned systems such as submarines, drones and robots"
  • Sách/Book

  • Machine learning for decision makers : cognitive computing fundamentals for better decision making

    • Authors: Patanjali Kashyap (2024)

  • This new and updated edition takes you through the details of machine learning to give you an understanding of cognitive computing, IoT, big data, AI, quantum computing, and more. The book explains how machine learning techniques are used to solve fundamental and complex societal and industry problems. This second edition builds upon the foundation of the first book, revises all of the chapters, and updates the research, case studies, and practical examples to bring the book up to date with changes that have occurred in machine learning. A new chapter on quantum computers and machine learning is included to prepare you for future challenges.
  • Sách/Book

  • Machine learning production systems engineering machine learning models and pipelines

    • Authors: Robert Crowe (2024)

  • This book provides four in-depth sections that cover all aspects of machine learning engineering: Data: collecting, labeling, validating, automation, and data preprocessing; data feature engineering and selection; data journey and storage Modeling: high performance modeling; model resource management techniques; model analysis and interoperability; neural architecture search Deployment: model serving patterns and infrastructure for ML models and LLMs; management and delivery; monitoring and logging Productionalizing: ML pipelines; classifying unstructured texts and images; genAI model pipelines
  • Sách/Book

  • Java and Algorithmic Thinking for the Complete Beginner learn to think like a programmer

    • Authors: Aristides S. Bouras (2024)

  • What you will learn Understand the fundamentals of how computers work Master Java programming basics and IDEs Develop proficiency in handling operators, and trace tables Implement sequence and decision control structures in programming Manipulate numbers, strings, and complex expressions Utilize arrays, HashMaps, and other data structures effectively Who this book is for This course is perfect for complete beginners with no prior programming experience, including high school students and hobbyists. It is also suitable for those with a basic understanding of computers who wish to deepen their knowledge of Java and algorithmic thinking
  • Sách/Book

  • 100 java mistakes and how to avoid them.

    • Authors: Tagir Valeev (2024)

  • 100 Java Mistakes and How To Avoid Them highlights 100 Java coding errors—from beginner missteps to mistakes even Java experts don’t know they’re making. Each case includes clear examples to show you what to look for and concrete troubleshooting advice. You’ll learn to use static analysis tools like IntelliJ IDEA and SonarLint to ensure you’re consistently delivering exceptional Java, discover how unit tests and defensive coding can keep your code clean, and even learn to write your own bug-busting plugins