The Hiring course of consisted of two rounds :
- Technical Spherical (45min)
- Educating Spherical (30min)
1) Within the first spherical, the interviewer requested me if I had a previous expertise in Machine Studying, about my initiatives subsequent he requested me to implement Linear Regression to transform Celsius to fahrenheit and print its output on a Celsius worth, its intercept, and slope.
Subsequent, he requested me fundamental Machine Studying and Information Science questions and you must sort it on Google doc precisely the way in which you’d write for a scholar :Â
- What’s L1 and L2 regularization?
- What’s the dropout layer?
- What’s the central restrict theorem?
- What are the methods to keep away from overfitting in Choice Tree?Â
- How does splitting occur in Choice Tree?
2) Within the subsequent spherical, you’re given 3 subjects (Choice Tree, Backpropagation, PCA) and choose one subject to arrange and train the interviewer. **You aren’t given a lot time to arrange**
I selected Choice Tree and ready slides for it. You’ll be able to train on a writing pad too.
Mainly after you train the interviewer, he got here up with some follow-up questions like why can we use log2 within the Entropy system?
How do you deal with knowledge with Choice Tree if it has each numerical and Classification knowledge?Â
Is Choice Tree parametric or non-parametric?
and a few questions associated to the slides I ready.
This spherical checks extra the way you deal with follow-up questions and never what you reply
