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    Effective Amazon Machine Learning. Expert web services for machine learning on cloud

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Effective Amazon Machine Learning. Expert web services for machine learning on cloud Alexis Perrier - okładka ebooka

    Effective Amazon Machine Learning. Expert web services for machine learning on cloud Alexis Perrier - okładka ebooka

    Effective Amazon Machine Learning. Expert web services for machine learning on cloud Alexis Perrier - okładka audiobooka MP3

    Effective Amazon Machine Learning. Expert web services for machine learning on cloud Alexis Perrier - okładka audiobooks CD

    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    306
    Dostępne formaty:
    PDF
    ePub
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    Ebook

    159,00 zł

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    Do przechowalni

    Predictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. Following AWS simplifying Machine learning, this book will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection.

    This book will introduce you to the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Furthermore, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK.

    Towards the end of the book, you will also learn how to apply these services to other problems, such as text mining, and to more complex datasets.

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    O autorze ebooka

    Alexis Perrier is a data science consultant with experience in signal processing and stochastic algorithms. He holds a master's in mathematics from Universit Pierre et Marie Curie Paris VI and a PhD in signal processing from Tlcom ParisTech. He is actively involved in the DC data science community. He is also an avid book lover and proud owner of a real chalk blackboard, where he regularly shares his fascination of mathematical equations with his kids.

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