How can you reduce overfitting of a random forest model?
Scientist Interviews
Scientist Interview Questions
"The questions you are asked in an interview for a position as a scientist will depend greatly on field of science you intend to work in. Generally, interviewers will be interested in your formal education, field of study and specialization, work, internship, and research experience, scientific writing skills, and interest in the subject matter. Expect to be asked technical questions that pertain to the knowledge needed to perform the duties of the job. While there are some positions open to scientists who possess associates' or bachelors' degrees, most jobs will require you to have at least a masters' degree with the majority requiring you to have a doctorate."
54,387 scientist 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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