Название: Machine Learning System Design Interview: An Insider's Guide
Автор: Ali Aminian, Alex Xu
Издательство: ByteByteGo
Год: 2023
Страниц: 254
Язык: английский
Формат: pdf (true)
Размер: 15.4 MB

Machine Learning system design interviews are the most difficult to tackle of all technical interview questions. This book provides a reliable strategy and knowledge base for approaching a broad range of ML system design questions. It provides a step-by-step framework for tackling an ML system design question. It includes many real-world examples to illustrate the systematic approach, with detailed steps you can follow.

We have written this book because we want to help Machine Learning (ML) engineers and data scientists to succeed at ML system design interviews. This book can also be helpful for those who want to achieve a high-level conception of how ML is applied in the real world.

Many engineers think of ML algorithms such as logistic regression or neural networks as the entirety of an ML system. However, an ML system in production involves much more than just model development. ML systems are typically complex, consisting of a number of components, including data stacks to manage data, serving infrastructure to make the system available to millions of users, an evaluation pipeline to measure the performance of the proposed system, and monitoring to ensure the model's performance doesn't degrade over time.

This book is an essential resource for anyone interested in ML system design, whether they are beginners or experienced engineers. Meanwhile, if you need to prepare for an ML interview, this book is specifically written for you.

What’s inside?
- An insider’s take on what interviewers really look for and why.
- A 7-step framework for solving any ML system design interview question.
- 10 real ML system design interview questions with detailed solutions.
- 211 diagrams that visually explain how various systems work.