Machine Learning Interviews: Kickstart Your Machine Learning and Data Career
Susan Shu Chang
2024년 3월 · Gildan Media · 내레이터: Xifeng Brooks
headphones
오디오북
9시간 39분
무삭제
family_home
적용 가능
info
report검증되지 않은 평점과 리뷰입니다. 자세히 알아보기
57분 샘플이 필요한가요? 오프라인일 때를 비롯해 언제든지 들을 수 있습니다.
추가
오디오북 정보
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, and data scientist; 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; and prepare for interviews in statistics and machine learning theory by studying common interview questions.
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, and data scientist; 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; and prepare for interviews in statistics and machine learning theory by studying common interview questions.
저자 정보
Susan Shu Chang is a principal data scientist at Elastic (of Elasticsearch), with previous ML experience in fintech, telecommunications, and social platforms. Susan is an international speaker, with talks at six PyCons worldwide and keynotes at Data Day Texas, PyCon DE & PyData Berlin, and O'Reilly's AI Superstream.
오디오북 평가
의견을 알려주세요.
오디오북을 듣는 방법
스마트폰 및 태블릿
노트북 및 컴퓨터
Google Play에서 구입한 도서를 컴퓨터의 웹브라우저로 읽을 수 있습니다.
