{"product_id":"practical-machine-learning-for-streaming-data-with-python-design-develop-and-validate-online-or-incremental-machine-learning-models-in-a-streaming-9781484268667","title":"Practical Machine Learning for Streaming Data with Python: Design, Develop, and Validate Online or Incremental Machine Learning Models in a Streaming","description":"\u003cp\u003e • Author(s): Sayan Putatunda\u003cbr\u003e • Publisher: Apress\u003cbr\u003e • Publisher Imprint: Apress\u003cbr\u003e • BISAC: Artificial Intelligence - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eDesign, 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. \u003c\/p\u003e 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.\u003cp\u003e\u003c\/p\u003e 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.\u003cp\u003e\u003c\/p\u003e \u003cp\u003eYou will: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand machine learning with streaming data concepts\u003c\/li\u003e\n\u003cli\u003eReview incremental and online learning\u003c\/li\u003e\n\u003cli\u003eDevelop models for detecting concept drift\u003c\/li\u003e\n\u003cli\u003eExplore techniques for classification, regression, and ensemble learning in streaming data contexts\u003c\/li\u003e\n\u003cli\u003eApply best practices for debugging and validating machine learning models in streaming data context\u003c\/li\u003e\n\u003cli\u003eGet introduced to other open-source frameworks for handling streaming data.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Apress","offers":[{"title":"Paperback","offer_id":45132103975063,"sku":"9781484268667","price":2212.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781484268667.webp?v=1767906601","url":"https:\/\/atlanticbooks.com\/products\/practical-machine-learning-for-streaming-data-with-python-design-develop-and-validate-online-or-incremental-machine-learning-models-in-a-streaming-9781484268667","provider":"Atlantic Books","version":"1.0","type":"link"}