The book aim of Machine Learning interview questions is to determine a candidate's level of

knowledge and understanding of Machine Learning concepts, algorithms, and tools. These

types of interviews are often used by employers to assess an applicant's problem-solving

skills and technical proficiency in the field.

The scope of scope of this book Machine Learning interview questions can range from basic

to more complex topics, such as the fundamentals of supervised and unsupervised learning,

working with data sets and libraries, building ML models, and deploying and monitoring ML

systems. Additionally, the interviewer may ask questions about the candidate's experience

with specific Machine Learning frameworks, data science techniques, and software

engineering practices.

Overall, this book helps to assess the candidate's level of knowledge and experience in the

field of Machine Learning. As such, it is important for the interviewer to ask questions that

are relevant to the job and the candidate's qualifications, as well as to provide a supportive

environment where the candidate can demonstrate their skillset.