Machine Learning Interviews: Kickstart Your Machine Learning and Data Career (Paperback)

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process.

Having served as principal data scientist in several companies, Chang has considerable experience as both ML interviewer and interviewee. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way. You'll quickly understand how to successfully navigate your way through typical ML interviews.

This guide shows you how to:

• Explore various machine learning roles, including ML engineer, applied scientist, data scientist, and other positions
• Assess your interests and skills before deciding which ML role(s) to pursue
• Evaluate your current skills and close any gaps that may prevent you from succeeding in the interview process
• Acquire the skill set necessary for each machine learning role
• Ace ML interview topics, including coding assessments, statistics and machine learning theory, and behavioral questions
• Prepare for interviews in statistics and machine learning theory by studying common interview questions

隨著科技產品在今天變得更加普及，對機器學習專業人員的需求也不斷增長。然而，不同公司對機器學習專業人員的責任和技能要求仍然存在很大差異，這使得面試過程難以預測。在這本指南中，數據科學領導者Susan Shu Chang將向您展示如何應對機器學習招聘過程。

作為幾家公司的首席數據科學家，Chang在機器學習面試官和應聘者的角色上都有豐富的經驗。她將通過分享她在這一過程中學到的寶貴經驗，帶領您穿越這個高度選擇性的招聘過程。您將迅速了解如何成功應對典型的機器學習面試。

本指南將向您展示如何：
- 探索各種機器學習角色，包括機器學習工程師、應用科學家、數據科學家和其他職位
- 在決定追求哪些機器學習角色之前，評估自己的興趣和技能
- 評估您目前的技能，並填補可能阻礙您在面試過程中成功的任何差距
- 獲取每個機器學習角色所需的技能
- 在機器學習面試中表現出色，包括編程評估、統計和機器學習理論以及行為問題
- 通過研究常見的面試問題，為統計和機器學習理論的面試做好準備