Important RGPV Question
AL-503(C), Optimization Techniques in Machine Learning
V Sem, AL
UNIT 1
Q.1 Define optimization and explain its importance in machine learning.
Q.2 What is Linear Programming? How is it formulated?
Q.3 Solve a given Linear Programming Problem (LPP) using the Simplex Method.
Q.4 Explain the role of limits and multivariate functions in optimization.
Q.5 How are derivatives and linear approximations used in single-variable and multi-variable functions for optimization?
UNIT 2
Q.1 What is Machine Learning readiness? Why is it important in optimization techniques?
Q.2 Explain the concept of risk mitigation in machine learning projects.
Q.3 Discuss the role of an experimental mindset in machine learning strategy.
Q.4 Compare the Build, Buy, and Partner strategies for setting up a machine learning project.
Q.5 How can you communicate and manage change effectively in a machine learning system?
UNIT 3
Q.1 What does “AI for good” mean? Discuss its importance in responsible machine learning.
Q.2 Explain positive and negative feedback loops in optimization with examples.
Q.3 How do metric design and observing behaviors influence machine learning models?
Q.4 What are secondary effects of optimization, and how can they impact machine learning projects?
Q.5 Discuss regulatory concerns associated with optimization in machine learning.
UNIT 4
Q.1 Explain the challenges of integrating machine learning into information systems.
Q.2 How do users affect the performance of machine learning models in production?
Q.3 Discuss time and space complexity in machine learning production systems.
Q.4 How do you decide when to retain or replace a machine learning model in production?
Q.5 What is ML model versioning, and why is it important?
UNIT 5
Q.1 What are the common post-deployment challenges faced by machine learning models?
Q.2 Explain QUAM (Quality, Usefulness, Accessibility, Maintainability) monitoring and logging in machine learning.
Q.3 Discuss the process of QUAM testing and maintenance for machine learning models.
Q.4 Why is it important to separate the data stack from production systems?
Q.5 What are the essential elements of a dashboard for metrics monitoring in machine learning?
— Best of Luck for Exam —
