Inside the Machine Learning Interview: 151 Real Questions from FAANG and How to Answer Them (機器學習面試全攻略：151道來自FAANG的真實問題及解答技巧)

Peng Shao

Inside the Machine Learning Interview: 151 Real Questions from FAANG and How to Answer Them
  • 出版商: Independent Publisher
  • 出版日期: 2023-05-09
  • 售價: $1,800
  • 貴賓價: 9.5 折 $1,710
  • 語言: 英文
  • 頁數: 314
  • 裝訂: Paperback
  • ISBN: 9798394054303
  • ISBN-13: 9798394054303
  • 相關分類: Machine Learning、面試技巧

    • 立即出貨(限量) (庫存=1)

相關主題

商品描述

Let Peng Shao, a former engineering leader at Amazon and Staff ML Engineer at Twitter, be your guide to mastering Machine Learning interviews in this comprehensive 314-page resource.


Inside, you'll find:
 

  • Comprehensive breakdown of the ML interview process, including all the major interview sessions: ML Fundamentals, ML Coding, ML System Design, & ML Infrastructure.
  • Proven strategies for approaching and solving a wide range of ML problems, drawing from real-world scenarios.
  • Step-by-step guidance on tackling ML coding challenges, system design questions, and infrastructure design problems.
  • Deep dive into the mindset of interviewers, understanding what they value and how to effectively demonstrate your expertise.
  • Practical examples and case studies showcasing the history of solutions to ML problems, from pioneering approaches to the state of the art.


 

商品描述(中文翻譯)

讓前亞馬遜工程領導和推特機器學習工程師彭少（Peng Shao）成為您在這本全面的314頁資源中掌握機器學習面試的指南。

內容包括：
- 對機器學習面試過程的全面分解，包括所有主要的面試環節：機器學習基礎、機器學習編碼、機器學習系統設計和機器學習基礎設施。
- 經過驗證的策略，用於處理和解決各種機器學習問題，從現實世界的情境中獲取。
- 逐步指導處理機器學習編碼挑戰、系統設計問題和基礎設施設計問題。
- 深入了解面試官的心態，了解他們重視什麼以及如何有效地展示您的專業知識。
- 實際例子和案例研究，展示解決機器學習問題的歷史，從開創性方法到最新技術。

請注意，以上為純文字翻譯，已移除 HTML code。

作者簡介

Peng Shao:

Peng Shao has over a decade of ML leadership experience spanning diverse industries such as social media, e-commerce, and finance. He is a former Staff ML Engineer at Twitter. He was a founding team member of Amazon Alexa, where he oversaw the speech recognition services behind the Echo and Fire TV. He also spearheaded the ML and NLP development for FactSet Fundamentals, a leading fintech product, and co-founded Roxy, a venture-backed AI startup that was acquired in 2019.IndependentlyIndependently

作者簡介(中文翻譯)

彭劭：



彭劭擁有超過十年的機器學習領導經驗，涵蓋社交媒體、電子商務和金融等多個行業。他曾是Twitter的一名高級機器學習工程師。他是Amazon Alexa的創始團隊成員之一，負責Echo和Fire TV背後的語音識別服務。他還領導了FactSet Fundamentals的機器學習和自然語言處理開發，該產品是領先的金融科技產品，並且是Roxy的聯合創始人，該初創企業於2019年被收購。

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