“An essential resource for aspiring data scientists and AI professionals.”
–A reader
The PDF version of Deep Learning Interviews is available for free download here on arXiv.
Deep Learning Interviews is an essential resource for aspiring data scientists and AI professionals facing the competitive gauntlet of job interviews or graduate-level exams. Spanning nearly 400 pages, this comprehensive volume offers hundreds of fully solved problems from key AI topics, including information theory, Bayesian statistics, algorithmic differentiation, logistic regression, perceptrons, and convolutional neural networks.
Designed to sharpen your skills and deepen your understanding, it provides step-by-step solutions, clear diagrams, and detailed reasoning to make complex concepts intuitive.
Unlike typical technical references, Deep Learning Interviews frames its challenging problems within thought-provoking questions and engaging stories, enabling readers to confidently tackle interview questions and articulate answers with clarity.
Paperback / Ebook
“Meticulously curated inventory empowers readers to speak fluently on AI topics.”
–A reader
“A rigorous rehearsal tool for job-seekers and a well-organized overview for students.”
–A reader
Deep Learning Interviews: Hundreds of Fully Solved Job Interview Questions from a Wide Range of Key Topics in AI
Deep Learning Interviews is an essential resource for aspiring data scientists and AI professionals facing the competitive gauntlet of job interviews or graduate-level exams. Spanning nearly 400 pages, this comprehensive volume offers hundreds of fully solved problems from key AI topics, including information theory, Bayesian statistics, algorithmic differentiation, logistic regression, perceptrons, and convolutional neural networks.
What makes this book unique? Unlike typical technical references, Deep Learning Interviews frames its challenging problems within thought-provoking questions and engaging stories, enabling readers to confidently tackle interview questions and articulate answers with clarity. It serves as both a rigorous rehearsal tool for job-seekers and a well-organized overview for machine learning M.Sc./Ph.D. students, covering a core curriculum of practical mathematical and computational skills now essential in computer science education.
The book’s meticulously curated inventory empowers readers to speak fluently on topics like calculus, entropy, and deep learning theory, forging connections that become second nature. With a quantitative background, you’ll find the problem sets, formulas, and instructions not only stimulating but also transformative, equipping you with the indispensable ability to stand out in a crowded field. Whether you’re a postgraduate student, a job-seeker, or an experienced researcher, Deep Learning Interviews offers powerful advantages to secure your dream role in AI.
