Master in Data Science (SMS, TU) Fundamentals of Data Science Question Paper 2081 Nepal

Explain in brief the concept of learning through data and experience.

Define entropy. How is it used with decision tree?

Explain why data ethics is crucial in data science.

What is deep learning? How is it similar or different from neural network.

Write short notes on:

a) Bias blind spot

b) Predictive Analytics

Explain the working mechanism of KNN algorithm for classification and regression.

OR

Explain the forward propagation and backward propagation of neural networks.

What do you mean by Random Forests? Why is random forest commonly used for feature selection despite being a machine learning model? Is random forest prone to overfitting? Why or why not?

What do you mean by support vectors? Explain with appropriate example of your own how supports vectors are useful in machine learning?

Apply map-reduce to the following set of data:

Data, Science, Engineering

Engineering, Data, Analytics

Analytics, Intelligence, Science

OR

What is Hadoop? Explain the different components of Hadoop.

A healthcare organization developed a machine learning model to predict patients' risk of developing certain medical conditions based on their electronic health records (EHR). The model was trained using historical patient data, including diagnoses, treatments, and outcomes. However, it was later discovered that the model exhibited bias against patients from lower socioeconomic backgrounds. The training data disproportionately represented patients from wealthier neighborhoods who had better access to healthcare services and resources. As a result, the model erroneously associated higher socioeconomic status with lower health risks, leading to underestimating the risk of certain conditions for patients from disadvantaged backgrounds.