Book Image

Production-Ready Applied Deep Learning

By : Tomasz Palczewski, Jaejun (Brandon) Lee, Lenin Mookiah
Book Image

Production-Ready Applied Deep Learning

By: Tomasz Palczewski, Jaejun (Brandon) Lee, Lenin Mookiah

Overview of this book

Machine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment. The main objective of this book is to close the gap between theory and applications by providing a thorough explanation of how to transform various models for deployment and efficiently distribute them with a full understanding of the alternatives. First, you will learn how to construct complex deep learning models in PyTorch and TensorFlow. Next, you will acquire the knowledge you need to transform your models from one framework to the other and learn how to tailor them for specific requirements that deployment environments introduce. The book also provides concrete implementations and associated methodologies that will help you apply the knowledge you gain right away. You will get hands-on experience with commonly used deep learning frameworks and popular cloud services designed for data analytics at scale. Additionally, you will get to grips with the authors’ collective knowledge of deploying hundreds of AI-based services at a large scale. By the end of this book, you will have understood how to convert a model developed for proof of concept into a production-ready application optimized for a particular production setting.
Table of Contents (19 chapters)
1
Part 1 – Building a Minimum Viable Product
6
Part 2 – Building a Fully Featured Product
10
Part 3 – Deployment and Maintenance

Summary

You have reached the final phase of your DL project. In this chapter, we described the steps you need to follow to wrap up the project. We first described how to apply PIR to evaluate the project and understand the potential improvements. In this phase, you also need to make sure the artifacts generated from the project are organized and thoroughly documented so that they can be reused for the next project. Lastly, we would like to mention that celebration is another key component of a DL project. All the stakeholders have put in their efforts to carry out the project. You must spend some time thanking all the team members and applauding their achievements.

Throughout this book, you have learned how to carry out a DL project at a high standard. Starting from the basic concepts in DL, we have described each phase of a DL project thoroughly, along with various tools you can use to carry out the task at hand efficiently. The book emphasizes scalability and explains how you...