Machine Learning Interviews: Kickstart Your Machine Learning and Data Career
Susan Shu Chang
бер. 2024 р. · Gildan Media · Озвучення: Xifeng Brooks
headphones
Аудіокнига
9 год 39 хв
Повна
family_home
Можна додати
info
reportGoogle не перевіряє оцінки й відгуки. Докладніше.
Хочете отримати зразок на 57 хв? Слухайте будь-коли, навіть не в мережі.
Додати
Про цю аудіокнигу
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.
Про автора
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.
Оцініть цю аудіокнигу
Повідомте нас про свої враження.
Інформація щодо прослуховування
Смартфони та планшети
Установіть додаток Google Play Книги для Android і iPad або iPhone. Він автоматично синхронізується з вашим обліковим записом і дає змогу читати книги в режимах онлайн і офлайн, де б ви не були.
Портативні та настільні комп’ютери
Придбані в Google Play книги можна читати за допомогою веб-переглядача вашого комп’ютера.
