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Autor(en): 
  • Nikita Silaparasetty
  • Machine Learning Concepts with Python and the Jupyter Notebook Environment: Using Tensorflow 2.0 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  September 2020  
    Genre:  EDV / Informatik 
     
    DeepLearning / jupyternotebook / machinelearning / python / TensorFlow
    ISBN:  9781484259665 
    EAN-Code: 
    9781484259665 
    Verlag:  Apress 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 18 mm 
    Gewicht:  487 gr 
    Seiten:  320 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebook instead of a text editor or a regular IDE. You'll start by learning how to use Jupyter Notebooks to improve the way you program with Python. After getting a good grounding in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book. Those who are new to machine learning can dive in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier. What You Will LearnProgram in Python and TensorFlow Tackle basic machine learning obstacles Develop in the Jupyter Notebooks environment Who This Book Is For Ideal for Machine Learning and Deep Learning enthusiasts who are interested in programming with Python using Tensorflow 2.0 in the Jupyter Notebook Application. Some basic knowledge of Machine Learning concepts and Python Programming (using Python version 3) is helpful.

      



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