Téléchargez le livre : Practical Machine Learning for Streaming Data with Python

Practical Machine Learning for Streaming Data with Python

Design, Develop, and Validate Online Learning Models

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Apress


Paru le : 2021-04-09



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Description

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.



What You'll Learn
Understand machine learning with streaming data conceptsReview incremental and online learningDevelop models for detecting concept driftExplore techniques for classification, regression, and ensemble learning in streaming data contextsApply best practices for debugging and validating machine learning models in streaming data contextGet introduced to other open-source frameworks for handling streaming data.

Who This Book Is For


Machine learning engineers and data science professionals
Pages
118 pages
Collection
n.c
Parution
2021-04-09
Marque
Apress
EAN papier
9781484268667
EAN PDF
9781484268674
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
2150 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
62,11 €
EAN EPUB
9781484268674
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
1382 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
62,11 €

Dr. Sayan Putatunda is an experienced data scientist and researcher. He holds a Ph.D. in Applied Statistics/ Machine Learning from the Indian Institute of Management, Ahmedabad (IIMA) where his research was on streaming data and its applications in the transportation industry. He has a rich experience of working in both senior individual contributor and managerial roles in the data science industry with multiple companies such as Amazon, VMware, Mu Sigma, and more. His research interests are in streaming data, deep learning, machine learning, spatial point processes, and directional statistics. As a researcher, he has multiple publications in top international peer-reviewed journals with reputed publishers. He has presented his work at various reputed international machine learning and statistics conferences. He is also a member of IEEE.



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