Machine learning

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data.

This book is aimed at practitioners of data science, with consideration for bespoke problems, standards, and tech stacks between industries.

Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

This is the first book completely dedicated to positioning and navigation using machine learning methods.

Put the power of AWS Cloud machine learning services to work in your business and commercial applications!

This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California.

This book explores how visualization provides an effective way of improving not only the interpretability but also the generalization capabilities of machine learning models.

Insightful projects to master deep learning and neural network architectures using Python and KerasKey FeaturesExplore deep learning across computer vision, natural language processing (NLP), and image processingDiscover best practices for the training of deep neural networks and their deploymentAccess popular deep learning models as well as widely used neural network architecturesBook DescriptionDeep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.

This book presents recent improvements in peridynamic modeling of structures.

This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications.

This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models.

This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management.

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications.

This book provides a first course on deep learning in computational mechanics.

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020.

Think about your data intelligently and ask the right questionsKey FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook DescriptionData cleaning is the all-important first step to successful data science, data analysis, and machine learning.

Hawkes processes are studied and used in a wide range of disciplines: mathematics, social sciences, and earthquake modelling, to name a few.

This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented fifth-generation (5G) and beyond core networks.

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge.

Understand how neural networks work and learn how to implement them using TensorFlow 2.

This book constitutes revised and selected papers from the scientific satellite events held in conjunction with the18th International Conference on Service-Oriented Computing, ICSOC 2020.

This book highlights a comprehensive overview of the recent advancements and challenges in the field of cybersecurity with a focus on the integration of artificial intelligence (AI), machine learning (ML), and blockchain technologies.

Desire is a term often used in conjunction with the subject.

This book constitutes the refereed proceedings of the 12th International Conference on Computer Vision Systems, ICVS 2019, held in Thessaloniki, Greece, in September 2019.

Solving problems with deep neural networks typically relies on massive amounts of labeled training data to achieve high performance/b>.

Get to know the why and how of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding.

The discovery in 2012 of the Higgs boson at the Large Hadron Collider (LHC) represents a milestone for the Standard Model (SM) of particle physics.

This book explores the integration of Generative AI within the Banking, Financial Services, and Insurance (BFSI) sector, elucidating its implications, applications, and the future landscape of BFSI.

This book describes how human hearing works and how to build machines that analyze sounds in the same way that people do.

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist.

The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of "e;big data"e; availability and advanced data science.

This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners.

Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipesKey FeaturesUse PyTorch 1.

With the intriguing development of technologies in several industries, along with the advent of ubiquitous computational resources, there are now ample opportunities to develop innovative computational technologies in order to solve a wide range of issues concerning uncertainty, imprecision, and vagueness in various real-life problems.

Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learning business solutions.

This book digs into the important confluence of cybersecurity and big data, providing insights into the ever-changing environment of cyber threats and solutions to protect these enormous databases.

A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.

This book constitutes thoroughly reviewed, revised and selected papers from the 5th International Conference on Human Centered Computing, HCC 2019, held in Cacak, Serbia, in August 2019.

This textbook presents deep learning models and their healthcare applications.

Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines.

Cutting-edge machine learning principles, practices, and applicationsThis comprehensive textbook explores the theoretical under pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems.

This book addresses emerging issues concerning the integration of artificial intelligence systems in our daily lives.

This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases.

Disruption resulting from the proliferation of AI is coming.

This book presents an overview of the latest smart transportation systems, IoV connectivity frameworks, issues of security and safety in VANETs, future developments in the IoV, technical solutions to address key challenges, and other related topics.

The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020.