Are you looking for NPTEL Introduction to Machine Learning Assignment Week 12 Answers? If yes, you will find the answers to the questions asked in the NPTEL Introduction to Machine Learning quiz exam here. If you are preparing for this exam this article will help you in finding the latest and updated answers.
There is a total of 7 questions related to Learning Theory, Introduction to Reinforcement Learning, and Optional videos (RL framework, TD learning, Solution Methods, Applications). The correct answers are marked in Green Color with a tick sign.
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NPTEL Introduction to Machine Learning Assignment Week 12 Answers
1. You have been recruited as a lead engineer by ArrEll corporation which wants to enter the self-driving car market. In the context of the standard Reinforcement Leaming framework, what would you classify as the state and actions? Note that your system does not have access to previous states.
2. After completing Introduction to Machine Leaming on NPTEL, you have landed a job as a Data Scientist at YumEll Solutions Inc. Your first assignment as a trainee is to learn a classifier given some data and present insights on it to your manager, who apparentily doesn’t seem to have any knowledge on Machine Learning. Which of the following classification models would you pick to best explain the nature of the data and the underlying distribution to your manager?
3. What happens when your model complexity (such as interaction terms in linear regression, order of polynomial in SVM, etc.) increases?(multiple options may be Corfect)
4. In the context of Reinforcement Learning algorithms, which of the following definitions constitutes a valid Markov State? (multiple options may be correct)
5. Suppose we want an RL agent to learn to play the game of golf. For training purposes, we make use of a golf simulator program. Assume that the original reward distribution gives a reward of +10 when the golf ball is hit into the hole and -1 for all other transitions. To aid the agent’s learning process, we propose to give an additional reward of +3 whenever the ball is within a 1 metre radius of the hole. Is this additional reward a good idea or not? Why?
6. You waht to toss a fair coin a number of times and obtain the probability of getting heads by taking a simple average. What is the estimated number of times you’ll have to toss the coin to make sure that your estimated probability is within 10% of the actual probability, at least 90% of the time?
7. You face a particularily challenging RL problem, where the reward distribution keeps changing with time. In order to gain maximum reward in this scenario, does it make sense to stop exploration or continue exploration?
NPTEL Introduction to Machine Learning Course is an online free course by IIT Madras that has been developed by Prof. Balaraman Ravindran. The main aim of this course is to provide the basic concepts of machine learning from a mathematically well-motivated perspective.
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