How To Use Ibm Cloud Object Storage When Building And Operating Cloud Native Applications
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How to Use IBM Cloud Object Storage When Building and Operating Cloud Native Applications
This IBM® RedpaperTM publication presents a series of tutorials for cloud native developers just getting started with IBM CloudTM and IBM Cloud Object Storage. Within the context of a car insurance application, this paper presents an introductory series of linked modules that allow developers unfamiliar with either IBM Cloud or cloud native development to get started with application development using IBM starter kits. This allows you to become familiar with the types of services available on IBM Cloud, and to develop a sense of which patterns and choices are appropriate for different use cases. Some of the technologies and products covered in this book are Cloudant®, WatsonTM Analytics, machine learning, elastic search, Kubernetes, containers, pre-signed URLs, Aspera®, and SQL Query. In addition to the technical integration steps, it also presents a business case for integrating these technologies and products with IBM Cloud Object Storage. The target audience for this paper is cloud native developers and cloud object storage specialists.
How to Use IBM Cloud Object Storage When Building and Operating Cloud Native Applications
This IBM® RedpaperTM publication presents a series of tutorials for cloud native developers just getting started with IBM CloudTM and IBM Cloud Object Storage. Within the context of a car insurance application, this paper presents an introductory series of linked modules that allow developers unfamiliar with either IBM Cloud or cloud native development to get started with application development using IBM starter kits. This allows you to become familiar with the types of services available on IBM Cloud, and to develop a sense of which patterns and choices are appropriate for different use cases. Some of the technologies and products covered in this book are Cloudant®, WatsonTM Analytics, machine learning, elastic search, Kubernetes, containers, pre-signed URLs, Aspera®, and SQL Query. In addition to the technical integration steps, it also presents a business case for integrating these technologies and products with IBM Cloud Object Storage. The target audience for this paper is cloud native developers and cloud object storage specialists.
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. - Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems - Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems - Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others - Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients