Deep Learning Interviews book: Hundreds of fully solved job interview questions (github.com)

Article summary

The article presents a book called 'Deep Learning Interviews' which contains hundreds of fully solved job interview questions from a wide range of key topics in AI. The book is designed to help postgraduate students and job seekers prepare for interviews and provide a well-organized overview of the field. It covers topics such as information theory, Bayesian statistics, and deep learning theory. The book is available for download and purchase through various channels.

Main themes

• Deep Learning Interviews book
• Data Science job interviews
• AI and ML theory
• Interview preparation
• Data Science role definitions
• Reinforcement Learning
• Binary Search and programming skills

What commenters say

• Data science and ML interviews can be tough due to the difficulty in preparing for everything and covering all the theory.
• Some interview questions, such as trick SQL questions or implementing binary search, may not be relevant to real-world data science work.
• The term 'data science' has expanded to mean different things and now encompasses a range of job profiles.
• Binary search is a surprisingly tricky problem that can be used to test a candidate's programming skills, but may not be the best indicator of their abilities.
• The use of certain interview questions, such as FizzBuzz, can be effective in weeding out unqualified candidates without punishing those who have non-traditional backgrounds.
• Title inflation has led to the term 'data science' being applied to a wider range of roles, including those that were previously considered analyst positions.
• The book 'Deep Learning Interviews' is a valuable resource for those preparing for interviews, but may benefit from additional sections on topics such as reinforcement learning.
• The interview process for data science and ML positions can be challenging and may require candidates to have a strong foundation in theory as well as practical skills.