Machine Learning Interviews: Kickstart Your Machine Learning and Data Career
Susan Shu Chang
2024. g. marts · Gildan Media · Ierunātājs: Xifeng Brooks
headphones
Audiogrāmata
9 h 39 min
nesaīsināta
family_home
Piemērota
info
reportAtsauksmes un vērtējumi nav pārbaudīti. Uzzināt vairāk
Vai vēlaties iegūt fragmentu (57 min)? Klausieties jebkurā laikā — pat bezsaistē.
Pievienot
Par šo audiogrāmatu
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.
Par autoru
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.
Novērtējiet šo audiogrāmatu
Izsakiet savu viedokli!
Informācija par klausīšanos
Viedtālruņi un planšetdatori
Instalējiet lietotni Google Play grāmatas Android ierīcēm un iPad planšetdatoriem/iPhone tālruņiem. Lietotne tiks automātiski sinhronizēta ar jūsu kontu un ļaus lasīt saturu tiešsaistē vai bezsaistē neatkarīgi no jūsu atrašanās vietas.
Klēpjdatori un galddatori
Varat lasīt pakalpojumā Google Play iegādātās grāmatas, izmantojot datora tīmekļa pārlūkprogrammu.
