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Autor(en): 
  • Mehdi Roopaei
  • Manuel Amunategui
  • Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2018  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / B / Big Data / Cloud Hosting / Computer Communication Networks / Computer communication systems / Databases / Datenbanken
    ISBN:  9781484238721 
    EAN-Code: 
    9781484238721 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D  
    Gewicht:  986 gr 
    Seiten:  482 
    Illustration:  XLI, 482 p. 319 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book-Amazon, Microsoft, Google, and PythonAnywhere.

    You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time.

    Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book.

    What You'll Learn

    • Extend your machine learning models using simple techniques to create compelling and interactive web dashboards
    • Leverage the Flask web framework for rapid prototyping of your Python models and ideas
    • Create dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more
    • Harness the power of TensorFlow by exporting saved models into web applications
    • Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored content
    • Create dashboards with paywalls to offer subscription-based access
    • Access API data such as Google Maps,OpenWeather, etc.
    • Apply different approaches to make sense of text data and return customized intelligence
    • Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back
    • Utilize the freemium offerings of Google Analytics and analyze the results
    • Take your ideas all the way to your customer's plate using the top serverless cloud providers

    Who This Book Is For

    Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.

      



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