Interpretable Machine Learning with Python
Learn to build interpretable high-performance models with hands-on real-world examples
This hands-on book will help you make your machine learning models fairer, safer, and more reliable and in turn improve business outcomes. Every chapter introduces a new mission where you learn how to apply interpretation methods to realistic use cases with methods that work for any model type as well as methods specific for deep neural networks. Les mer
479,-
E-bok
Tilgjengelig umiddelbart etter kjøp
This hands-on book will help you make your machine learning models fairer, safer, and more reliable and in turn improve business outcomes. Every chapter introduces a new mission where you learn how to apply interpretation methods to realistic use cases with methods that work for any model type as well as methods specific for deep neural networks.
Detaljer
- Forlag
- Packt Publishing Limited
- Språk
- Engelsk
- ISBN
- 9781800206571
- Utgivelsesår
- 2021
- Format
- Kopibeskyttet EPUB (Må leses i Adobe Digital Editions)
Om forfatteren
Serg Masís has been at the confluence of the internet, application development, and analytics for the last two decades. Currently, he's a climate and agronomic data scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co-founded a start-up, incubated by Harvard Innovation Labs, that combined the power of cloud computing and machine learning with principles in decision-making science to expose users to new places and events. Whether it pertains to leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often-missing link between data and decision-making—and machine learning interpretation helps bridge this gap robustly.