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Machine Learning with LightGBM and Python

You're reading from   Machine Learning with LightGBM and Python A practitioner's guide to developing production-ready machine learning systems

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781800564749
Length 252 pages
Edition 1st Edition
Languages
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Author (1):
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Andrich van Wyk Andrich van Wyk
Author Profile Icon Andrich van Wyk
Andrich van Wyk
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Gradient Boosting and LightGBM Fundamentals
2. Chapter 1: Introducing Machine Learning FREE CHAPTER 3. Chapter 2: Ensemble Learning – Bagging and Boosting 4. Chapter 3: An Overview of LightGBM in Python 5. Chapter 4: Comparing LightGBM, XGBoost, and Deep Learning 6. Part 2: Practical Machine Learning with LightGBM
7. Chapter 5: LightGBM Parameter Optimization with Optuna 8. Chapter 6: Solving Real-World Data Science Problems with LightGBM 9. Chapter 7: AutoML with LightGBM and FLAML 10. Part 3: Production-ready Machine Learning with LightGBM
11. Chapter 8: Machine Learning Pipelines and MLOps with LightGBM 12. Chapter 9: LightGBM MLOps with AWS SageMaker 13. Chapter 10: LightGBM Models with PostgresML 14. Chapter 11: Distributed and GPU-Based Learning with LightGBM 15. Index 16. Other Books You May Enjoy

References

[1]

N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, “SMOTE: Synthetic Minority Over-sampling Technique,” Journal of Artificial Intelligence Research, vol. 16, p. 321–357, June 2002.

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