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Machine Learning with LightGBM and Python

Machine Learning with LightGBM and Python

By : Andrich van Wyk
4.4 (8)
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Machine Learning with LightGBM and Python

Machine Learning with LightGBM and Python

4.4 (8)
By: Andrich van Wyk

Overview of this book

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.
Table of Contents (17 chapters)
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1
Part 1: Gradient Boosting and LightGBM Fundamentals
6
Part 2: Practical Machine Learning with LightGBM
10
Part 3: Production-ready Machine Learning with LightGBM

An introduction to AWS and SageMaker

This section provides a high-level overview of AWS and delves into SageMaker, AWS’ ML offering.

AWS

AWS is one of the leading players in the global cloud computing marketplace. AWS offers many cloud-based products and services, including databases, machine learning (ML), analytics, networking, storage, developer tools, and enterprise applications. The idea behind AWS is to offer businesses an affordable and scalable solution to their computing needs, regardless of their size or industry.

A key advantage of AWS is elasticity, meaning servers and services can be stopped and started quickly and at will, scaling from zero machines to thousands. The elasticity of the services goes hand in hand with its primary pricing model of pay-as-you-go, meaning customers only pay for the services and resources they use without any upfront costs or long-term contracts. This elasticity and pricing allow businesses to scale computing needs as needed...

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