Introduction to Machine Learning

Question 1

Why is machine learning becoming mainstream and essential for IT professionals?

Answer 1

They use collections of large amounts of data to gain insight and predict trends.

Question 2

What is a dedicated module for machine learning within Apache Spark?

Answer 2

Spark ML

Question 3

What does Spark ML do?

Answer 3

Spark ML is a dedicated module for machine learning within Apache Spark, integrating machine learning algorithms with Big Data for speed and distributed computation.

Question 4

What is the process for Machine Learning?

Answer 4

Data collection, feature engineering, algorithm selection, model training/evaluation, and live analysis.

Question 5

What are the types of algorithms?

Answer 5

Supervised and Unsupervised.

Question 6

What are Supervised algorithms?

Answer 6

Regression and classification.

Question 7

What are unsupervised algorithms?

Answer 7

Clustering.

Question 8

What is Feature Engineering?

Answer 8

Supervised learning involves inputs (features/independent variables) and outputs (labels/dependent variables).

Question 9

What are the steps in Feature Engineering?

Answer 9

Data cleaning, feature analysis, feature preparation, and feature scaling.

Question 10

What is Linear Regression used for?

Answer 10

Linear regression is used to predict a continuous value.

Question 11

What are some of the methods in Linear Regression and what do they do?

Answer 11

Ordinary Least Squares Method: Minimizes the sum of squared errors to find the best-fit line.

Multivariate regression: involves predicting a label using multiple features.

Accurate measurement: coefficient of determination measures how well the model fits the data.