Machine Learning with LightGBM and Python: A practitioner's guide to developing production-ready machine learning systems

Andrich van Wyk

zł59.99 ~~zł161.99~~

4.4 (8 Ratings)

eBook Sep 2023 252 pages 1st Edition

Andrich van Wyk

zł59.99 ~~zł161.99~~

4.4 (8 Ratings)

eBook Sep 2023 252 pages 1st Edition

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Key benefits

Get started with LightGBM, a powerful gradient-boosting library for building ML solutions
Apply data science processes to real-world problems through case studies
Elevate your software by building machine learning solutions on scalable platforms
Purchase of the print or Kindle book includes a free PDF eBook

Description

Machine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.

Who is this book for?

This book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.

What you will learn

Get an overview of ML and working with data and models in Python using scikit-learn
Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS
Master LightGBM and apply it to classification and regression problems
Tune and train your models using AutoML with FLAML and Optuna
Build ML pipelines in Python to train and deploy models with secure and performant APIs
Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Om S Oct 10, 2023

"Machine Learning with LightGBM and Python" is a fantastic guide for both beginners and experienced folks. It introduces you to the powerful LightGBM framework, making machine learning easier. You'll learn about decision trees, gradient boosting, and more in simple language. The book takes you through practical case studies, so you can use machine learning to solve real problems.As you progress, you'll even learn how to build and scale your machine learning systems using tools like FastAPI and AWS Sagemaker. It's perfect for anyone who wants to improve their machine learning skills. You should know some Python, but you don't need to be an expert. This book is your key to understanding LightGBM and mastering machine learning.In short, it's a great book for those who want to excel in machine learning and build production-ready systems.

Amazon Verified review

H2N Oct 16, 2023

"Machine Learning with LightGBM and Python" is a detailed guide tailored for both newcomers and experts in machine learning. It sheds light on the LightGBM framework, emphasizing hands-on experience with key concepts like decision trees and gradient boosting. The book starts with foundational machine learning topics, then ventures into ensemble learning, showcasing algorithms like random forests. It prominently features LightGBM, comparing its strengths with other methods like XGBoost and deep neural networks. The text also explores hyperparameter optimization using Optuna, offers practical case studies, and introduces AutoML via FLAML. Transitioning from theory to application, it discusses ML pipelines, MLOps, AWS SageMaker, and harnessing distributed computing with LightGBM. This book is a comprehensive roadmap for mastering machine learning with Python and LightGBM.

Amazon Customer Nov 09, 2023

The book strikes a good balance between theory and practical applications, ensuring that readers understand both the underlying principles and their real-world relevance. The code examples are well-structured and easy to follow, making it effortless for readers to implement the concepts discussed in the book. particularly appreciated the chapter on bagging and boosting which is the principle of LightGBM. The book also covers various evaluation metrics and hyperparameter tuning, providing readers with a comprehensive understanding of model optimization. While the book focuses on Light GBM, it also touches upon other important machine learning concepts, ensuring readers have a well-rounded understanding of the field.Overall, "Machine Learning with Light GBM and Python" is a valuable resource for anyone interested in leveraging the power of Light GBM in their machine learning projects. Whether you're a beginner or an experienced practitioner, this book will equip you with the knowledge and practical skills needed to excel in the field of machine learning.

Sangita Mahala Nov 29, 2023

I strongly suggest this book for individuals who possess an interest in data, a proficiency in Python programming, and a curiosity to delve into the diverse realm of machine learning with LightGBM. It will undoubtedly enhance their skill set.

Steven Fernandes Oct 29, 2023

This book offers a comprehensive introduction to machine learning (ML) with a focus on Python and scikit-learn. It guides readers through various ML techniques, including decision trees, ensemble learning, and advanced methods like gradient boosting, DART, and GOSS. Special attention is given to mastering LightGBM for both classification and regression challenges. The book also emphasizes the importance of AutoML tools like FLAML and Optuna for model optimization. Readers will learn to construct ML pipelines for efficient training and deployment, and how to scale their ML solutions using AWS Sagemaker, PostgresML, and Dask for production-level applications.

Machine Learning with LightGBM and Python: A practitioner's guide to developing production-ready machine learning systems

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