Book

Machine Learning for Streaming Data with Python

This book will help you to design, develop and implement machine learning models for streaming data to generate real-time insights. You’ll also be able to explore the challenges associated with streaming data and its best practices.

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Difficulty Level

Intermediate

Completion Time

8h36m

Language

English

About Book

Who Is This Book For?

This book is for data scientists and machine learning engineers who have a background in machine learning, are practice and technology-oriented, and want to learn how to apply machine learning to streaming data through practical examples with modern technologies. Although an understanding of basic Python and machine learning concepts is a must, no prior knowledge of streaming is required.

Book content

chapters 8h36m total length

An Introduction to Streaming Data

Architectures for Streaming and Real-Time Machine Learning

Data Analysis on Streaming Data

Online Learning with River

Online Anomaly Detection

Online Classification

Online Regression

Reinforcement Learning

Drift and Drift Detection

Feature Transformation and Scaling

Catastrophic Forgetting

Conclusion and Best Practices

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