Apress | Practical Machine Learning For Streaming Data With Python: Design, Develop, And Validate Online Learning Models (2021 EN)

Author: Sayan Putatunda
Full Title: Practical Machine Learning For Streaming Data With Python: Design, Develop, And Validate Online Learning Models
Publisher: Apress; 1st ed. edition (April 9, 2021)
Year: 2021
ISBN-13: 9781484268674 (978-1-4842-6867-4), 9781484268667 (978-1-4842-6866-7)
ISBN-10: 1484268679, 1484268660
Pages: 118
Language: English
Genre: Educational: Machine Learning
File type: EPUB (True), PDF (True), Code Files
Quality: 10/10
Price: 37.44 €


Design, develop, and validate machine learning models with streaming data using the Scikit-Multiflow framework. This book is a quick start guide for data scientists and machine learning engineers looking to implement machine learning models for streaming data with Python to generate real-time insights.

You'll start with an introduction to streaming data, the various challenges associated with it, some of its real-world business applications, and various windowing techniques. You'll then examine incremental and online learning algorithms, and the concept of model evaluation with streaming data and get introduced to the Scikit-Multiflow framework in Python. This is followed by a review of the various change detection/concept drift detection algorithms and the implementation of various datasets using Scikit-Multiflow.

Introduction to the various supervised and unsupervised algorithms for streaming data, and their implementation on various datasets using Python are also covered. The book concludes by briefly covering other open-source tools available for streaming data such as Spark, MOA (Massive Online Analysis), Kafka, and more.


Learn:
✓ Understand machine learning with streaming data concepts
✓ Review incremental and online learning
✓ Develop models for detecting concept drift
✓ Explore techniques for classification, regression, and ensemble learning in streaming data contexts
✓ Apply best practices for debugging and validating machine learning models in streaming data context
✓ Get introduced to other open-source frameworks for handling streaming data.

Features:
✓ Explains the latest Scikit-Multiflow framework in detail
✓ Explains Supervised and Unsupervised Learning for streaming data
✓ One of the first books in the market on machine learning models for streaming data using Python

Who This Book Is For:
Machine learning engineers and data science professionals.

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