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Machine Learning for Streaming Data with Python. Rapidly build practical online machine learning solutions using River and other top key frameworks Joos Korstanje

Język publikacji: angielskim
Machine Learning for Streaming Data with Python. Rapidly build practical online machine learning solutions using River and other top key frameworks Joos Korstanje - okladka książki

Machine Learning for Streaming Data with Python. Rapidly build practical online machine learning solutions using River and other top key frameworks Joos Korstanje - okladka książki

Autor:
Joos Korstanje
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
258
Dostępne formaty:
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     ePub

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Streaming data is the new top technology to watch out for in the field of data science and machine learning. As business needs become more demanding, many use cases require real-time analysis as well as real-time machine learning. This book will help you to get up to speed with data analytics for streaming data and focus strongly on adapting machine learning and other analytics to the case of streaming data.
You will first learn about the architecture for streaming and real-time machine learning. Next, you will look at the state-of-the-art frameworks for streaming data like River. Later chapters will focus on various industrial use cases for streaming data like Online Anomaly Detection and others. As you progress, you will discover various challenges and learn how to mitigate them. In addition to this, you will learn best practices that will help you use streaming data to generate real-time insights.
By the end of this book, you will have gained the confidence you need to stream data in your machine learning models.

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O autorze książki

Joos Korstanje, with his master’s degrees in both environmental sciences and data science, has been working on statistics and data science for almost ten years. Through his work in different companies including Disney, Axa, and others, he has closely followed the developments in data science and related fields. This experience in the business world allows him to write about data science from an applied point of view (through his books, Medium, Towards Data Science, LinkedIn, and more).

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