Azure AI Services at Scale for Cloud, Mobile, and Edge: Building Intelligent Apps with Azure Cognitive Services and Machine Learning, Bisson Simon, Branscombe Mary, Hoder Chris
Автор: Janusz Bedkowski Название: Large-Scale Simultaneous Localization and Mapping ISBN: 9811919712 ISBN-13(EAN): 9789811919718 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is dedicated for engineers and researchers who would like to increase the knowledge in area of mobile mapping systems.
Описание: Machine learning allows models or systems to learn without being explicitly programmed. You will see how to use the best of libraries support such as scikit-learn, Tensorflow and much more to build efficient smart systems.
Автор: Dipanjan Sarkar; Raghav Bali; Tushar Sharma Название: Practical Machine Learning with Python ISBN: 1484232062 ISBN-13(EAN): 9781484232064 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully.
Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code.
Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered.
Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment.
Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem.
Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today
What You'll Learn
Execute end-to-end machine learning projects and systems
Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks
Review case studies depicting applications of machine learning and deep learning on diverse domains and industries
Apply a wide range of machine learning models including regression, classification, and clustering.
Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning.
Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students
Автор: Sergio Escalera; Markus Weimer Название: The NIPS `17 Competition: Building Intelligent Systems ISBN: 3030068676 ISBN-13(EAN): 9783030068677 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Нет в наличии.
Описание: This book summarizes the organized competitions held during the first NIPS competition track. It provides both theory and applications of hot topics in machine learning, such as adversarial learning, conversational intelligence, and deep reinforcement learning.Rigorous competition evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and management procedure. This book contains the chapters from organizers on competition design and from top-ranked participants on their proposed solutions for the five accepted competitions: The Conversational Intelligence Challenge, Classifying Clinically Actionable Genetic Mutations, Learning to Run, Human-Computer Question Answering Competition, and Adversarial Attacks and Defenses.
Delve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python
Key Features
Understand how to obtain financial data via Quandl or internal systems
Automate commercial banking using artificial intelligence and Python programs
Implement various artificial intelligence models to make personal banking easy
Book Description
Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI.
You'll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you'll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you'll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you'll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you'll get to grips with some real-world AI considerations in the field of banking.
By the end of this book, you'll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI.
What you will learn
Automate commercial bank pricing with reinforcement learning
Perform technical analysis using convolutional layers in Keras
Use natural language processing (NLP) for predicting market responses and visualizing them using graph databases
Deploy a robot advisor to manage your personal finances via Open Bank API
Sense market needs using sentiment analysis for algorithmic marketing
Explore AI adoption in banking using practical examples
Understand how to obtain financial data from commercial, open, and internal sources
Who this book is for
This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.
Название: Building Intelligent Systems ISBN: 1484234316 ISBN-13(EAN): 9781484234310 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Part 1: Approaching an Intelligent System Project.-
Chapter 1: Introducing Intelligent Systems.-
Chapter 2: Knowing When to Use Intelligent Systems.-
Chapter 3: A Brief Refresher on Working with Data.-
Chapter 4: Defining the Intelligent System's Goals.-
Part 2: Intelligent Experiences.-
Chapter 5: The Components of Intelligent Experiences.-
Chapter 6: Why Creating Intelligence Experiences Is Hard.-
Chapter 7: Balancing Intelligent Experiences.-
Chapter 8: Modes of Intelligent Interaction.-
Chapter 9: Getting Data from Experience.-
Chapter 10: Verifying Intelligent Experiences.-
Part 3: Implementing Intelligence.-
Chapter 11: The Components of an Intelligence Implementation.-
Chapter 12: The Intelligence Runtime.-
Chapter 13: Where Intelligence Lives.-
Chapter 14: Intelligence Management.-
Chapter 15: Intelligent Telemetry.-
Part 4: Creating Intelligence.-
Chapter 16: Overview of Intelligence.-
Chapter 17: Representing Intelligence.-
Chapter 18: The Intelligence Creation Process.-
Chapter 19: Evaluating Intelligence.-
Chapter 20: Machine Learning Intelligence.-
Chapter 21: Organizing Intelligence.-
Part 5: Orchestrating Intelligent Systems.-
Chapter 22: Overview of Intelligence Orchestration.-
Chapter 23: The Intelligence Orchestration Environment.-
Chapter 24: Dealing with Mistakes.-
Chapter 25: Adversaries and Abuse.-
Chapter 26: Approaching Your Own Intelligent System.-
Автор: Sergio Escalera; Markus Weimer Название: The NIPS `17 Competition: Building Intelligent Systems ISBN: 3319940414 ISBN-13(EAN): 9783319940410 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book summarizes the organized competitions held during the first NIPS competition track. It provides both theory and applications of hot topics in machine learning, such as adversarial learning, conversational intelligence, and deep reinforcement learning.Rigorous competition evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and management procedure. This book contains the chapters from organizers on competition design and from top-ranked participants on their proposed solutions for the five accepted competitions: The Conversational Intelligence Challenge, Classifying Clinically Actionable Genetic Mutations, Learning to Run, Human-Computer Question Answering Competition, and Adversarial Attacks and Defenses.
Описание: This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making.
Автор: Chakraborty Rajdeep, Ghosh Anupam, Mandal Jyotsna Kumar Название: Machine Learning Techniques and Analytics for Cloud Security ISBN: 1119762251 ISBN-13(EAN): 9781119762256 Издательство: Wiley Рейтинг: Цена: 29771.00 р. Наличие на складе: Нет в наличии.
Описание: MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY
This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions
The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively.
Audience
Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.
Автор: Artasanchez Alberto, Joshi Prateek Название: Artificial Intelligence with Python - Second Edition ISBN: 183921953X ISBN-13(EAN): 9781839219535 Издательство: Неизвестно Рейтинг: Цена: 10114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Completely updated and revised edition of the bestselling guide to artificial intelligence, updated to Python 3.8 and TensorFlow 2, with seven new chapters that cover RNNs, AI & Big Data, fundamental use cases, machine learning data pipelines, chatbots, Big Data, and more.
Автор: Gupta Punit, Goyal Mayank Kumar, Chakraborty Sudeshna Название: Machine Learning and Optimization Models for Optimization in Cloud ISBN: 1032028203 ISBN-13(EAN): 9781032028200 Издательство: Taylor&Francis Рейтинг: Цена: 20671.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cloud computing has been a new trend in problem-solving and providing reliable computing platform for big and high computational tasks. This technique is used for business industries like banking, trading and many e-commerce businesses to accommodate high request rate, high availability for all time without stopping system and system failure.
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