Feature Engineering Bookcamp

Feature Engineering Bookcamp
Sinan Ozdemir
RRP:
NZ$ 123.99
Our Price:
NZ$ 116.55
Paperback
h235 x 187mm - 272pg
4 Oct 2022
International import eta 7-19 days
9781617299797
Out Of Stock
Currently no stock in-store, stock is sourced to your order
Quantity:
 
 
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

In stock - for items in stock we aim to dispatch the next business day. For delivery in NZ allow 2-5 business days, with rural taking a wee bit longer.

Locally sourced in NZ - stock comes from a NZ supplier with an approximate delivery of 7-15 business days.

International Imports - stock is imported into NZ, depending on air or sea shipping option from the international supplier stock can take 10-30 working days to arrive into NZ. 

Pre-order Titles - delivery will vary depending on where the title is published, if local stock is available in NZ then 5-7 business days, for international imports it can be 10-30 business days. In all cases we will access the quickest supply option.

Delivery Packaging - we ship all items in cardboard sleeves or by box with either packing paper or corn starch chips. (We avoid using plastics bubble bags)

Tracking - Orders are delivered by track and trace courier and are fully insured, tracking information will be sent by email once dispatched.

View our full Order & Delivery information