Imagine a Newly-Born starts to learn walking. It will try to find a suitable policy to learn walking after repeated falling and getting up.specify what type of machine learning is best suited?

Solution(By Examveda Team)

Imagine a newly-born starts to learn walking. It will try to find a suitable policy to learn walking after repeated falling and getting up. Specify what type of machine learning is best suited?

Option A: Classification
Classification is not the most suitable type of machine learning for this scenario. Classification typically involves assigning data points to predefined categories or classes. It may not capture the continuous and dynamic nature of learning to walk.

Option B: Regression
Regression involves predicting a continuous numerical output based on input features. While it allows for continuous predictions, it may not be the best fit for the scenario described, which involves learning a policy for walking rather than predicting specific values.

Option C: K-Means Algorithm
The K-Means algorithm is a clustering technique that is not suitable for learning to walk. It is used to partition data into clusters, which does not align with the concept of learning a policy for a dynamic task like walking.

Option D: Reinforcement Learning
Reinforcement learning is the most appropriate type of machine learning for the scenario described. It involves learning a policy through trial and error, where actions are taken in an environment to maximize rewards. In the context of a newborn learning to walk, this aligns with the process of repeated falling and getting up to find a suitable walking policy. So, Option D is the correct choice.

In summary, reinforcement learning is the most suitable type of machine learning for a newborn learning to walk, as it involves learning a policy through trial and error and maximizing rewards.