Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Hands-On Gradient Boosting with XGBoost and scikit-learn
Hands-On Gradient Boosting with XGBoost and scikit-learn

Hands-On Gradient Boosting with XGBoost and scikit-learn: Perform accessible machine learning and extreme gradient boosting with Python

eBook
$42.99
Paperback
$52.99
Subscription
Free Trial
Renews at $12.99p/m

What do you get with a Packt Subscription?

Free for first 7 days. $15.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Key benefits

  • Get up and running with machine learning and understand how to boost models with XGBoost in no time
  • Build real-world machine learning pipelines and fine-tune hyperparameters to achieve optimal results
  • Discover tips and tricks and gain innovative insights from XGBoost Kaggle winners

Description

XGBoost is an industry-proven, open-source software library that provides a gradient boosting framework for scaling billions of data points quickly and efficiently. The book introduces machine learning and XGBoost in scikit-learn before building up to the theory behind gradient boosting. You’ll cover decision trees and analyze bagging in the machine learning context, learning hyperparameters that extend to XGBoost along the way. You’ll build gradient boosting models from scratch and extend gradient boosting to big data while recognizing speed limitations using timers. Details in XGBoost are explored with a focus on speed enhancements and deriving parameters mathematically. With the help of detailed case studies, you’ll practice building and fine-tuning XGBoost classifiers and regressors using scikit-learn and the original Python API. You'll leverage XGBoost hyperparameters to improve scores, correct missing values, scale imbalanced datasets, and fine-tune alternative base learners. Finally, you'll apply advanced XGBoost techniques like building non-correlated ensembles, stacking models, and preparing models for industry deployment using sparse matrices, customized transformers, and pipelines. By the end of the book, you’ll be able to build high-performing machine learning models using XGBoost with minimal errors and maximum speed.

Who is this book for?

This book is for data science professionals and enthusiasts, data analysts, and developers who want to build fast and accurate machine learning models that scale with big data. Proficiency in Python, along with a basic understanding of linear algebra, will help you to get the most out of this book.

What you will learn

  • Build gradient boosting models from scratch
  • Develop XGBoost regressors and classifiers with accuracy and speed
  • Analyze variance and bias in terms of fine-tuning XGBoost hyperparameters
  • Automatically correct missing values and scale imbalanced data
  • Apply alternative base learners like dart, linear models, and XGBoost random forests
  • Customize transformers and pipelines to deploy XGBoost models
  • Build non-correlated ensembles and stack XGBoost models to increase accuracy

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 16, 2020
Length: 310 pages
Edition : 1st
Language : English
ISBN-13 : 9781839218354
Category :
Languages :

What do you get with a Packt Subscription?

Free for first 7 days. $15.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Oct 16, 2020
Length: 310 pages
Edition : 1st
Language : English
ISBN-13 : 9781839218354
Category :
Languages :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$12.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 6,500+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
$129.99 billed annually
Feature tick icon Unlimited access to Packt's library of 6,500+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts
$179.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 6,500+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total $ 165.97
Machine Learning with PyTorch and Scikit-Learn
$54.99
Machine Learning for Algorithmic Trading
$57.99
Hands-On Gradient Boosting with XGBoost and scikit-learn
$52.99
Total $ 165.97 Stars icon
Visually different images

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7
(7 Ratings)
5 star 71.4%
4 star 28.6%
3 star 0%
2 star 0%
1 star 0%
Filter icon Filter
Top Reviews

Filter reviews by




Justin R McCormick Sep 22, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have dabbled here and there in Machine Learning/Neural Networks. This book has brought more of an understanding to the concepts for me before page 100. Recommended.
Amazon Verified review Amazon
Omar Kamal Hosney May 17, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
That is one of the best books that I have ever read.
Amazon Verified review Amazon
Peter Grace Dec 11, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The writing style here where you build and step through sklearn trees to XGBoost is superb. I haven’t read another ml text that flows as well as this. XGBoost is arguably the tool for tabular data and this book will get you applying it to good purpose, fast. I hope Corey can find the time to keep publishing more books like this to continue to help make accessible the important topics of machine learning and data insight.
Amazon Verified review Amazon
Justin Nov 23, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
If you’re just starting out with XGBoost or machine learning, you will not regret purchasing this book. The theory + code makes this a must have. Wish I would’ve found it sooner!
Amazon Verified review Amazon
Pujun Mar 04, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I think the book is great for anyone who wants to get to speed about the fundamental techniques related to Gradient boosting and also learn about scikit-learn. Complete disclosure: I have a graduate degree in computer science ( AI ) and I currently work as a Machine Learning engineer in the Silicon Valley. I read the book for learning scikit-learn and also just refresh some of the concepts about boosting that I had learned during graduate school but had not used them in the last 2 years or so.The book has plenty of examples and resources that not only show how to implement the algorithm but also goes over when is the right time to use such an algorithm ( the pros and cons of the approaches ) and also how to implement it using scikit-learn, a pretty popular python package.Would definitely recommend the book
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.