| 书目名称 | Ensemble Learning for AI Developers | | 副标题 | Learn Bagging, Stack | | 编辑 | Alok Kumar,Mayank Jain | | 视频video | | | 概述 | Explains ensemble learning with less math and more programming-friendly abstractions than presented in other books so it is easier for you to learn.Discusses the competitive edge that you can achieve | | 图书封面 |  | | 描述 | Use ensemble learning techniques and models to improve your machine learning results..Ensemble Learning for AI Developers. starts you at the beginning with an historical overview and explains key ensemble techniques and why they are needed. You then will learn how to change training data using bagging, bootstrap aggregating, random forest models, and cross-validation methods. Authors Kumar and Jain provide best practices to guide you in combining models and using tools to boost performance of your machine learning projects. They teach you how to effectively implement ensemble concepts such as stacking and boosting and to utilize popular libraries such as Keras, Scikit Learn, TensorFlow, PyTorch, and Microsoft LightGBM. Tips are presented to apply ensemble learning in different data science problems, including time series data, imaging data, and NLP. Recent advances in ensemble learning are discussed. Sample code is provided in the form of scripts and the IPython notebook..What You Will Learn.Understand the techniques and methods utilized in ensemble learning.Use bagging, stacking, and boosting to improve performance of your machine learning projects by combining models to decrease | | 出版日期 | Book 2020 | | 关键词 | Ensemble Learning; Machine Learning; Regression; Supervised Learning; Artificial Intelligence; Python; Dee | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-5940-5 | | isbn_softcover | 978-1-4842-5939-9 | | isbn_ebook | 978-1-4842-5940-5 | | copyright | Alok Kumar and Mayank Jain 2020 |
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发表于 2025-3-21 16:29:20
