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Top 33 Optimisation Interview Questions
Entry Junior Mid Senior Expert
Optimisation Theoretical Questions
Q1:
What is Optimisation in Machine Learning?
Entry
Q2:
What are Bayesian Optimization Methods?
Junior
Q3:
Related To: ML Design Patterns, Dimensionality Reduction
When would you use Grid Search vs Random Search for Hyperparameter Tuning?
Related To: ML Design Patterns, Dimensionality Reduction Junior
Q4:
Related To: ML Design Patterns, Model Evaluation, Dimensionality Reduction
What methods of Hyperparameters Tuning do you know?
Related To: ML Design Patterns, Model Evaluation, Dimensionality Reduction Junior
Q5:
What are Differentiable Objective Functions?
Junior
Q6:
What are Non-Differentiable Objective Functions?
Junior
Q7:
Why do you need to know Convex Optimization?
Junior
Mid Mid Mid Q11:
Why does Newton's Method only use First and Second Derivatives, not Third or Higher Derivatives?
Mid Q12:
How is AdaGrad used to optimize a Learning Rate?
Mid Q13:
Related To: Gradient Descent
When Optimizing a Neural Network, how do you define the Termination Condition for Gradient Descent?
Related To: Gradient Descent Mid Q14:
Related To: Neural Networks
When you are Optimizing a Neural Network, does it make sense to combine both Momentum and Weight Decay to improve the performance?
Related To: Neural Networks Mid Mid Q16:
How do you use the Convex Optimization Approach to Minimize Regret?
Mid Q17:
What is Random Search Optimization?
Mid Mid Q19:
Why is Newton's Method not used in Optimisation as opposed to Gradient Descent?
Mid Q20:
How Bayesian Optimisation is used in Hyperparameter Tuning?
Senior Q21:
Why is Newton's Method not sensitive to ill-conditioned Hessian?
Senior Senior Q23:
Related To: Neural Networks
Should Training Samples Randomly Drawn for Mini-Batch Training Neural Networks be drawn with or without Replacement?
Related To: Neural Networks Senior Q24:
Related To: Gradient Descent
For both Convex, and Non-Convex Problems, does the Gradient in SGD always point to the global extreme value?
Related To: Gradient Descent Senior Q25:
Related To: Neural Networks
When you are Optimizing your Neural Network, is it a good idea to Prune the Network?
Related To: Neural Networks Senior Q26:
Related To: Gradient Descent
In what situations would you prefer Coordinate Descent over Gradient Descent?
Related To: Gradient Descent Senior Q27:
Related To: Random Forest
In Random Forests, how do you optimize the Number of Trees T in the Forest?
Related To: Random ForestT in the Forest? Senior Q28:
In Hyperparameter Optimization, would you use Random Search or Grid Search to achieve a better performance?
Senior Q29:
Related To: Gradient Descent
Explain in detail how Momentum-based Gradient Descent and Nesterov's Accelerated Gradient Descent work
Related To: Gradient Descent Senior Q30:
Related To: Gradient Descent
What is the difference between Momentum based Gradient Descent and Nesterov's Accelerated Gradient Descent?
Related To: Gradient Descent Senior Q31:
Compare using Newton's Method and Gradient Descent for Optimisation
Senior Q32:
What does "almost all local minimum have very similar function value to the global optimum" mean?
Expert Q33:
What is an Optimization Strategy which can be used to solve Convex Problems but is Blind to the Problem Structure?
Expert 
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