1. Explain supervised and unsupervised ML 2. Scenario-based questions and which ML algorithm to use 3. Justify your answers
Machine Learning Intern Interview Questions
8,203 machine learning intern interview questions shared by candidates
Comment faire du fine tuning d'un LLM ?
Describe RAG , how it works
standard format with Leetcode type questions with test cases, a couple of design rounds. However expectation setting was very poor.
Reverse the string Several ML questions - what is bias and variance, what is the difference between classification and regression, What is the effect on the output feature maps of the convolution layer that follows a max pooling layer. Why do we want a maxpooling layer. When to use a confusion matrix. What is the difference between precision, recall and F1. what is focal loss, what is dice loss. ML System Design (Facial recognition system) - think about clustering, dimensionality reduction, database storage, approximate nearest neighbor search, reducing database lookup time with horizontal scaling. Also think about feature/concept drift detection and rectification. Talk briefly about knowledge distillation, model quantization and pruning. Data engineering question - how would you remove duplicate images? Hash the images using a fingerprinting algorithm using DFT. Similar to how shazam's audio fingerprinting works. Now you have reduced the problem to removing duplicate fingerprints. If you type "image hashing" in google, a lot of academic papers with noise robust algorithms will pop up.
Please introduce your project in your resume.
Q:How would you design a machine learning system for automatically straighten the rotated photos in a dataset?
About your CV/ resume, work
Two eggs and a 100 story building puzzle.
1. Find if a string has balanced paranthesis 2. Basic ML questions (ML algos, evaluation etc)
Viewing 1601 - 1610 interview questions