How can you reduce overfitting of a random forest model?
Data Science Engineer Interview Questions
40,366 data science engineer interview questions shared by candidates
Technical depth in deep learning and machine learning. Thorough understanding of my relevant work experience in machine learning and data science.
1. How to Predict Room Occupancy Based on Environmental Factors. 2. Wine quality using knn 3. vanishing gradient problem 4. Which of activation function can’t be used at output layer to classify an image ? 5. Is K-fold cross-validation linear in K, quadratic in K, cubic in K or exponential in K?
Q. Change the sigmoid function so that it is more narrow?
What do you think one challenge Heetch is facing currently, and how do you plan to solve it?
Explain the projects done in the previous company
Problem-solving. In-depth questions from previous projects and skill set. A strong grasp of fundamentals is necessary. Why you used certain techniques and algorithms over others?
Does the dependent variable in regression need to be normally distributed?
Describe a project you've been working on.
Initial screening round with basics on machine learning like overfitting, design a system for the use case. current knowledge of various algorithms. Interview with researcher went on in deep theory of ML and DS/Algo question.
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