ok2.txt

What’s the trade-off between bias and variance?
What is the difference between supervised and unsupervised machine learning?
How is KNN different from k-means clustering?
Explain how a ROC curve works.
Define precision and recall.
What is Bayes’ Theorem? How is it useful in a machine learning context?
Why is “Naive” Bayes naive?
 Explain the difference between L1 and L2 regularization.
What’s your favorite algorithm, and can you explain it to me in less than a minute?
 What’s the difference between Type I and Type II error?
 What’s a Fourier transform?
What’s the difference between probability and likelihood?
What is deep learning, and how does it contrast with other machine algorithms?
What’s the difference between a generative and discriminative model?
What cross-validation technique would you use on a time series dataset?
How is a decision tree pruned?
 Which is more important to you: model accuracy or model performance?
What’s the F1 score? How would you use it?
How would you handle an imbalanced dataset?
When should you use classification over regression?
 Name an example where ensemble techniques might be useful.
How do you ensure you’re not overfitting with a model?
 What evaluation approaches would you work to gauge the effectiveness of a machine learning model?
How would you evaluate a logistic regression model?
What’s the “kernel trick” and how is it useful?
How do you handle missing or corrupted data in a dataset?
Do you have experience with Spark or big data tools for machine learning?
Pick an algorithm. Write the pseudo-code for a parallel implementation.
 What are some differences between a linked list and an array?
Describe a hash table.
: Which data visualization libraries do you use? What are your thoughts on the best data visualization tools?
How are primary and foreign keys related in SQL?
How does XML and CSVs compare in terms of size?
What are the data types supported by JSON? 
What do you think of our current data process?
What do you think of our current data process?