Download or read book Machine Learning in Python for Visual and Acoustic Data based Process Monitoring written by Ankur Kumar and published by MLforPSE. This book was released on 2024-04-24 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to help readers gain quick familiarity with deep learning-based computer vision and abnormal equipment sound detection techniques. The book helps you take your first step towards learning how to use convolutional neural networks (the ANN architecture that is behind the modern revolution in computer vision) and build image sensor-based manufacturing defect detection solutions. A quick introduction is also provided to how modern predictive maintenance solutions can be built for process critical equipment by analyzing the sound generated by the equipment. Overall, this short eBook sets the foundation with which budding process data scientists can confidently navigate the world of modern computer vision and acoustic monitoring.

Download or read book Python for Machine Learning and Natural Language Processing in Robotics and Autonomous Vehicles written by Mr. Akash Arun Kumar Soumya and published by BUDHA PUBLICATION. This book was released on with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: ..

Download or read book ECPPM 2021 eWork and eBusiness in Architecture Engineering and Construction written by Vitaly Semenov and published by CRC Press. This book was released on 2021-07-25 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: eWork and eBusiness in Architecture, Engineering and Construction 2021 collects the papers presented at the 13th European Conference on Product and Process Modelling (ECPPM 2021, Moscow, 5-7 May 2021). The contributions cover a wide spectrum of thematic areas that hold great promise towards the advancement of research and technological development targeted at the digitalization of the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. High quality contributions are devoted to critically important problems that arise, including: Information and Knowledge Management Semantic Web and Linked Data Communication and Collaboration Technologies Software Interoperability BIM Servers and Product Lifecycle Management Systems Digital Twins and Cyber-Physical Systems Sensors and Internet of Things Big Data Artificial and Augmented Intelligence in AEC Construction Management 5D/nD Modelling and Planning Building Performance Simulation Contract, Cost and Risk Management Safety and Quality Sustainable Buildings and Urban Environments Smart Buildings and Cities BIM Standardization, Implementation and Adoption Regulatory and Legal Aspects BIM Education and Training Industrialized Production, Smart Products and Services Over the past quarter century, the biennial ECPPM conference series, as the oldest BIM conference, has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry.

Download or read book Duetting and Turn Taking Patterns of Singing Mammals From Genes to Vocal Plasticity and Beyond written by Patrice Adret and published by Frontiers Media SA. This book was released on 2023-10-23 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mammalian vocal duets and turn-taking exchanges — long, coordinated acoustic signals exchanged between two individuals— are primarily found in family-living, pair-bonded mammals with a socially monogamous lifestyle (some rodents, some lemurs, tarsiers, titi monkeys, a Mentawai langur, gibbons and siamangs). Duetting and turn-taking patterns combine visual, chemical, tactile and auditory cues to produce some of the most exuberant displays in the realm of animal communication. How and why such phenotypes evolved independently across main lineages are fundamental questions at the core of the nature-nurture debate. Duetting styles ranging from antiphonal (non-overlapping) to simultaneous (overlapping) emissions have now been documented in various taxa, some of which are quite reminiscent of turn-taking rules in human conversation. Nonetheless, much remains to be learned about this complex motor skill, and at all four levels of analysis, namely (1) developmental processes, (2) causal mechanisms (3) functional properties and (4) evolutionary history. Given the strong link between this form of coordinated singing and pair-bonding, gaining a deeper understanding of this kind of cooperative behavior will likely shed more light on the deep evolutionary roots of human culture, language and music.

Download or read book Artificial Intelligence in Music Sound Art and Design written by Tiago Martins and published by Springer Nature. This book was released on 2022-04-15 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2022, held as part of Evo* 2022, in April 2022, co-located with the Evo* 2022 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 6 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

Download or read book Machine Learning Applications Using Python written by Puneet Mathur and published by Apress. This book was released on 2018-12-12 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you’ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You’ll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will LearnDiscover applied machine learning processes and principles Implement machine learning in areas of healthcare, finance, and retail Avoid the pitfalls of implementing applied machine learning Build Python machine learning examples in the three subject areas Who This Book Is For Data scientists and machine learning professionals.

Download or read book Machine Learning for Ecology and Sustainable Natural Resource Management written by Grant Humphries and published by Springer. This book was released on 2018-11-05 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.

Download or read book Complex Systems Spanning Control and Computational Cybernetics Applications written by Peng Shi and published by Springer Nature. This book was released on 2022-09-18 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, dedicated to Professor Georgi M. Dimirovski on his anniversary, contains new research directions, challenges, and many relevant applications related to many aspects within the broadly perceived areas of systems and control, including signal analysis and intelligent systems. The project comprises two volumes with papers written by well known and very active researchers and practitioners. The first volume is focused on more foundational aspects related to general issues in systems science and mathematical systems, various problems in control and automation, and the use of computational and artificial intelligence in the context of systems modeling and control. The second volume is concerned with a presentation of relevant applications, notably in robotics, computer networks, telecommunication, fault detection/diagnosis, as well as in biology and medicine, and economic, financial, and social systems too.

Download or read book Advances in haptic feedback for neurorobotics applications written by Guanghua Xu and published by Frontiers Media SA. This book was released on 2023-05-02 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Download or read book Frontiers in Signal Processing Editors Choice 2022 written by Augusto Sarti and published by Frontiers Media SA. This book was released on 2023-04-05 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

Download or read book Deep Learning Applications Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Download or read book Artificial Intelligence in Precision Health written by Debmalya Barh and published by Academic Press. This book was released on 2020-03-04 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available. This book is a valuable source for clinicians, healthcare workers, and researchers from diverse areas of biomedical field who may or may not have computational background and want to learn more about the innovative field of artificial intelligence for precision health. - Provides computational approaches used in artificial intelligence easily understandable for non-computer specialists - Gives know-how and real successful cases of artificial intelligence approaches in predictive models, modeling disease physiology, and public health surveillance - Discusses the applicability of AI on multiple areas, such as drug discovery, clinical trials, radiology, surgery, patient care and clinical decision support

Download or read book Python Machine Learning Projects written by Lisa Tagliaferri and published by DigitalOcean. This book was released on 2019-05-02 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: As machine learning is increasingly leveraged to find patterns, conduct analysis, and make decisions — sometimes without final input from humans who may be impacted by these findings — it is crucial to invest in bringing more stakeholders into the fold. This book of Python projects in machine learning tries to do just that: to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning to help ensure that it is serving us all. This book will set you up with a Python programming environment if you don’t have one already, then provide you with a conceptual understanding of machine learning in the chapter “An Introduction to Machine Learning.” What follows next are three Python machine learning projects. They will help you create a machine learning classifier, build a neural network to recognize handwritten digits, and give you a background in deep reinforcement learning through building a bot for Atari.

Download or read book Agile Technical Practices Distilled written by Pedro M. Santos and published by Packt Publishing Ltd. This book was released on 2019-06-28 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delve deep into the various technical practices, principles, and values of Agile. Key FeaturesDiscover the essence of Agile software development and the key principles of software designExplore the fundamental practices of Agile working, including test-driven development (TDD), refactoring, pair programming, and continuous integrationLearn and apply the four elements of simple designBook Description The number of popular technical practices has grown exponentially in the last few years. Learning the common fundamental software development practices can help you become a better programmer. This book uses the term Agile as a wide umbrella and covers Agile principles and practices, as well as most methodologies associated with it. You’ll begin by discovering how driver-navigator, chess clock, and other techniques used in the pair programming approach introduce discipline while writing code. You’ll then learn to safely change the design of your code using refactoring. While learning these techniques, you’ll also explore various best practices to write efficient tests. The concluding chapters of the book delve deep into the SOLID principles - the five design principles that you can use to make your software more understandable, flexible and maintainable. By the end of the book, you will have discovered new ideas for improving your software design skills, the relationship within your team, and the way your business works. What you will learnLearn the red, green, refactor cycle of classic TDD and practice the best habits such as the rule of 3, triangulation, object calisthenics, and moreRefactor using parallel change and improve legacy code with characterization tests, approval tests, and Golden MasterUse code smells as feedback to improve your designLearn the double cycle of ATDD and the outside-in mindset using mocks and stubs correctly in your testsUnderstand how Coupling, Cohesion, Connascence, SOLID principles, and code smells are all relatedImprove the understanding of your business domain using BDD and other principles for "doing the right thing, not only the thing right"Who this book is for This book is designed for software developers looking to improve their technical practices. Software coaches may also find it helpful as a teaching reference manual. This is not a beginner's book on how to program. You must be comfortable with at least one programming language and must be able to write unit tests using any unit testing framework.

Download or read book Machine Learning for Audio Image and Video Analysis written by Francesco Camastra and published by Springer. This book was released on 2015-07-21 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.