Details about Building Machine Learning Powered Applications Going From Idea to Product
Building Machine Learning Powered Applications PDF free download – Over the past decade, machine learning (ML) has increasingly been used to power a variety of products such as automated support systems, translation services, recommendation engines, fraud detection models, and many, many more.
Surprisingly, there aren’t many resources available to teach engineers and scientists how to build such products. Many books and classes will teach how to train ML models or how to build software projects, but few blend both worlds to teach how to build practical applications that are powered by ML.
Deploying ML as part of an application requires a blend of creativity, strong engineering practices, and an analytical mindset. ML products are notoriously challenging to build because they require much more than simply training a model on a dataset. Choosing the right ML approach for a given feature, analyzing model errors and data quality issues, and validating model results to guarantee product quality are all challenging problems that are at the core of the ML building process.
This book goes through every step of this process and aims to help you accomplish each of them by sharing a mix of methods, code examples, and advice from me and other experienced practitioners. We’ll cover the practical skills required to design, build, and deploy ML–powered applications. The goal of this book is to help you succeed at every part of the ML process.