Feature Engineering Bookcamp - Softcover

Ozdemir, Sinan

Softcover

ISBN 10: 1617299790 ISBN 13: 9781617299797

Publisher: Manning, 2022

Synopsis

Deliver huge improvements to your machine learning pipelines without spending hours fine-tuning parameters! This book’s practical case-studies reveal feature engineering techniques that upgrade your data wrangling—and your ML results.

In Feature Engineering Bookcamp you will learn how to:

    Identify and implement feature transformations for your data
    Build powerful machine learning pipelines with unstructured data like text and images
    Quantify and minimize bias in machine learning pipelines at the data level
    Use feature stores to build real-time feature engineering pipelines
    Enhance existing machine learning pipelines by manipulating the input data
    Use state-of-the-art deep learning models to extract hidden patterns in data

Feature Engineering Bookcamp guides you through a collection of projects that give you hands-on practice with core feature engineering techniques. You’ll work with feature engineering practices that speed up the time it takes to process data and deliver real improvements in your model’s performance. This instantly-useful book skips the abstract mathematical theory and minutely-detailed formulas; instead you’ll learn through interesting code-driven case studies, including tweet classification, COVID detection, recidivism prediction, stock price movement detection, and more.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Get better output from machine learning pipelines by improving your training data! Use feature engineering, a machine learning technique for designing relevant input variables based on your existing data, to simplify training and enhance model performance. While fine-tuning hyperparameters or tweaking models may give you a minor performance bump, feature engineering delivers dramatic improvements by transforming your data pipeline.

About the book
Feature Engineering Bookcamp walks you through six hands-on projects where you’ll learn to upgrade your training data using feature engineering. Each chapter explores a new code-driven case study, taken from real-world industries like finance and healthcare. You’ll practice cleaning and transforming data, mitigating bias, and more. The book is full of performance-enhancing tips for all major ML subdomains—from natural language processing to time-series analysis.

What's inside

    Identify and implement feature transformations
    Build machine learning pipelines with unstructured data
    Quantify and minimize bias in ML pipelines
    Use feature stores to build real-time feature engineering pipelines
    Enhance existing pipelines by manipulating input data

About the reader
For experienced machine learning engineers familiar with Python.

About the author
Sinan Ozdemir is the founder and CTO of Shiba, a former lecturer of Data Science at Johns Hopkins University, and the author of multiple textbooks on data science and machine learning.

Table of Contents
1 Introduction to feature engineering
2 The basics of feature engineering
3 Healthcare: Diagnosing COVID-19
4 Bias and fairness: Modeling recidivism
5 Natural language processing: Classifying social media sentiment
6 Computer vision: Object recognition
7 Time series analysis: Day trading with machine learning
8 Feature stores
9 Putting it all together

About this title

From the Back Cover

Kubernetes is an essential tool for anyone deploying and managing cloud-native applications. Kubernetes in Action, Second Edition is a fully-updated and comprehensive guide to developing and running applications in a Kubernetes environment. It lays out a complete introduction to container technologies and containerized applications along with practical tips for efficient deployment and operation. This revised edition of the bestselling original contains new coverage of the Kubernetes architecture, including the Kubernetes API, and a deep dive into managing a Kubernetes cluster in production. about the technology Kubernetes is Greek for "helmsman," your guide through unknown waters. The Kubernetes container orchestration system safely manages the structure and flow of a distributed application, organizing containers and services for maximum efficiency. Kubernetes serves as an operating system for your clusters, reducing the need to factor the underlying network and server infrastructure into your designs. As more and more applications are created using cloud-native and container-based architectures, Kubernetes has become an essential tool for modern developers to master. about the book Kubernetes in Action, Second Edition teaches you to use Kubernetes to deploy container-based distributed applications. You'll start with an overview of how Docker containers work with Kubernetes and move quickly to building your first cluster. You'll gradually expand your initial application, adding features and deepening your knowledge of Kubernetes architecture and operation. In this revised and expanded second edition, you'll take a deep dive into the structure of a Kubernetes-based application and discover how to manage a Kubernetes cluster in production. As you navigate this comprehensive guide, you'll also appreciate thorough coverage of high-value topics like monitoring, tuning, and scaling.

Edition details

• Publisher: Manning
• Publication date: 2022
• Language: English
• ISBN 10: 1617299790
• ISBN 13: 9781617299797
• Binding: Paperback
• Number of pages: 272