subject : Machine Learning

1- Differentiate Machine Learning, Deep Learning, Artificial Intelligence, Data Science and Natural Language Processing, Data mining with example application to each one.

2- Write a table of comparison for Linear regression- single and multi-variable, Logistic regression, KNN, Support Vector Machines, Decision Trees, and K-means in terms of algorithm description, process, evaluation, accuracy, advantages and dis-advantages.

3- Implement a K-means algorithm on real time-application, using available dataset.

4- Let's assume we want to play badminton on a particular day say Saturday how will you decide whether to play or not. Let's say you go out and check if it's hot or cold, check the speed of the wind and humidity, how the weather is, i.e. is it sunny, cloudy, or rainy. You take all these factors into account to decide if you want to play or not. Write a Observations of the last ten days and represent, predict accuracy for the concept Play Badminton.