Questions

1. What is machine learning and how it being used in the capital market? Explain in brief.

2. What is logistic regression and in which form does it generate its output?

3. Write a small piece of code to use a neural network for any stock time series.

4. How does a confusion matrix explain the accuracy of a model?

5. How do you standardize data and why is it important in the model building process?

6. How is support vector machine different from logistic regression?

7. Explain supervised and unsupervised learning and how to use these techniques in algorithmic trading.

8. Write a small piece of code for the k means algorithm using any one stock closing price.

9. Apart from confusionMatrix(), what is the other function to calculate classification and misclassification matrices?

10. What is the difference between decision tree and random forest and how are features selected from random forest?