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      1. Data och IT
      2. Systemvetenskap och AI

      Hands-On Machine Learning with IBM Watson

      Leverage IBM Watson to implement machine learning techniques and algorithms using Python

      AvJames D. Miller

      Häftad, Engelska, 2019

      584 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning servicesKey FeaturesImplement data science and machine learning techniques to draw insights from real-world dataUnderstand what IBM Cloud platform can help you to implement cognitive insights within applicationsUnderstand the role of data representation and feature extraction in any machine learning systemBook DescriptionIBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies.By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples.What you will learnUnderstand key characteristics of IBM machine learning servicesRun supervised and unsupervised techniques in the cloudUnderstand how to create a Spark pipeline in Watson StudioImplement deep learning and neural networks on the IBM Cloud with TensorFlowCreate a complete, cloud-based facial expression classification solutionUse biometric traits to build a cloud-based human identification systemWho this book is forThis beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.

      Produktinformation

      • Utgivningsdatum:2019-03-29
      • Mått:191 x 235 x 16 mm
      • Vikt:543 g
      • Format:Häftad
      • Språk:Engelska
      • Antal sidor:288
      • Förlag:Packt Publishing Limited
      • ISBN:9781789611854

      Utforska kategorier

      • Systemvetenskap och AI inom Data och IT

      Mer om författaren

      James D. Miller is an IBM certified expert, Master Consultant, Application/System Architect with +35 years of applications & system design/development experience across multiple platforms, technologies and data formats, including Big Data. His experience includes IBM Planning Analytics, BI, Web architecture & design, systems analysis, GUI design & testing, Data modeling, design, and development of OLAP, Client/Server, Web & Mainframe applications and systems utilizing: Planning Analytics Workspace (PAW), IBM Watson Analytics, Cognos BI & TM1, Framework Manager, dynaSight/ArcPlan, ASP, DHTML, XML, MS Visual Basic, VBA, PERL, R, SPLUNK, MS SQL Server, ORACLE, etc.He has authored numerous books, including Implementing Splunk - Second Edition; Mastering Splunk; Hands-On Machine Learning with IBM Watson; IBM Watson Projects; Statistics for Data Science; Mastering Predictive Analytics with R - Second Edition and others.Project areas include those with Data Analytics, Planning Analytics, and FOPM projects, holding various roles from architect, developer, technical and project leader.

      Innehållsförteckning

      • Table of ContentsIntroduction to IBM CloudFeature Extraction Supervised Machine Learning Models for Your DataImplementing Unsupervised AlgorithmsMachine Learning Workouts on IBM CloudUsing SPARK with IBM Watson StudioDeep Learning Using TensorFlow on the IBM CloudCreating a Facial Expression Platform on the IBM CloudAutomated Classification of Lithofacies Formation Using Machine LearningBuilding a Cloud-Based Multi-Biometric Identity Authentication Platform
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