Completed
- How do you handle missing or incomplete data in a machine learning project?
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Machine Learning Engineer Mock Interview for Meta with ChatGPT
Automatically move to the next video in the Classroom when playback concludes
- 1 - Intro
- 2 - ChatGPT Overview
- 3 - Interview Start
- 4 - Can you explain a specific machine learning project you have worked on?
- 5 - How do you handle missing or incomplete data in a machine learning project?
- 6 - How do you evaluate the performance of a machine learning model?
- 7 - Can you discuss a situation where you had to balance precision and recall in a model?
- 8 - What feature engineering techniques have you used and why?
- 9 - Write code in Python to generate a classification dataset with 3 classes and 5 features. You should be able to use the features to classify the examples.
- 10 - Use the dataset to train a 2-layer Neural Network with PyTorch
- 11 - Design a restaurant recommendation system
- 12 - You found that your system is overfitting. What might be the cause of that? What can you do to fix it?
- 13 - Will I recommend ChatGPT for Machine Learning Engineer?
- 14 - Giving ChatGPT feedback about the interview
