Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases

Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases

Kumar, Alok
Jain, Mayank

Paperback

General ComputersProgramming

Publisher Price: $49.99

ISBN10: 1484259394
ISBN13: 9781484259399
Publisher: Apress
Published: Jun 19 2020
Pages: 136
Weight: 0.50
Height: 0.33 Width: 6.14 Depth: 9.21
Language: English
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.

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