Machine Learning System Design Interview

Aminian, Ali; Xu, Alex

ISBN 10: 1736049127 / ISBN 13: 9781736049129

Editore: ByeByteGo, 2023

A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if youâ re not satisfied with purchase please return item for full refund. Ships via media mail. Codice articolo OTV.1736049127.G

Riassunto:

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.

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.

Table Of Contents
Chapter 1 Introduction and Overview
Chapter 2 Visual Search System
Chapter 3 Google Street View Blurring System
Chapter 4 YouTube Video Search
Chapter 5 Harmful Content Detection
Chapter 6 Video Recommendation System
Chapter 7 Event Recommendation System
Chapter 8 Ad Click Prediction on Social Platforms
Chapter 9 Similar Listings on Vacation Rental Platforms
Chapter 10 Personalized News Feed
Chapter 11 People You May Know

Dati bibliografici

Titolo: Machine Learning System Design Interview
Casa editrice: ByeByteGo
Data di pubblicazione: 2023
Legatura: Brossura
Condizione: good