A doubt on Introduction Quiz Test

Hi there,

As I was taking an Introduction Quiz, and I came across a following question which I didn’t clearly understand the answer. Could you please clarify for me?
Question: What are the roles of machines in Machine Learning?
Answer: “The role of machines in Machine Learning is to estimate the parameters.”
Here, we had different options - Collect data, Knowledge Representation and there was an another option which I don’t remember but, out of all, how does estimate the parameters the role of machines in Machine Learning?

Thank you!

Try to perceive questions related to machine learning in this perspective such as Data, Task, Model, Loss Functions, Learning Algorithms, and Evaluation.

The roles of human: [Data, Task, Model, Loss Functions]

As we have seen from the first week of the course the different steps involved in doing data science are to Collect, Store, Process, Describe and Model data. All these are or can only be decided by a human and not by a machine.

The stages such as collect, store, process and describe are essential to even see whether the data is compatible for a task or to even formulate a suitable task. Once the task is formulated by a human then again it is human who decides what model (whether statistical or machine learning or deep learning model) can be chosen for a particular task based on the experience of handling data. Same goes for choosing Loss Function.

Role of a machine: [Learning Algorithm]
But in the case of the learning algorithm, this is entirely up to the machine to learn the parameters associated with the features.

Think an example of say 1000 rows and 1000 columns or features to which you have chosen yourself to learn the parameters associated with the columns instead of machine learning algorithm learning it. What will happen? How will you relate between variables/features or say how will you say that these features have more weightage than other features and also they are related or unrelated? It will be a tedious task for a human right (that is to learn without the experience of handling and learning the weightage of the features). So, this is where machine learning algorithms come in rescue so that the complexity of human tackling such a task is reduced drastically. In this sense, the machine will learn here and all other tasks are handled by humans.

Summary: Machines (learns) are directed entirely by humans (dictates) where actions of a machine are the consequence of human knowledge.

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Thank you, Pradeep. You’ve helped me in clarifying my doubt.
Appreciate your time in this regard.

Thank you!

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Hi Moderator,

i scored 50% first week quiz, i see many questions which is not covered in Syallabus. As prerequite you said no prog experice required.


i missed valuable inputs in videos?

pls help what i need to learn to get 100% score in coming lecturers?

I scored this time 80% after lishening concepts again and again.

Last few chapters like: Myths of Data science and Diff Ai and Data science and Paths of Data science is very critical in clearning week 1 exam.

Hi @mc_raj4u,
Don’t worry, the grades will not be counted on certificate, you just need to pass them to move to next module. You can retry as many times as you want.


Thk you for that reply, by the way is there anything i can read more apart from padhai ai, so that i can grab concepts quickly finish the course,

I took almost Week 2 part 1 - 5 lessons - 6hrs. to digest topics.

Hi, These are just introductory topics, don’t worry now. You can just get into the course and if you find any particular topic difficult to understand, you can refer book Introductory Statistics by S.Ross.