Week 01 Lecture Content

Question 1

What is Machine Learning (Arthur Samuel)?

Answer 1

Definition: Machine Learning is the study of computer algorithms that improve automatically through experience according to a performance measure (1959).

Question 2

What is Machine Learning (Tom Mitchell)?

Answer 2

A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance in tasks T, as measured by P, improves with experience E (1998).

Question 3

What are the three major classes of Machine Learning?

Answer 3

Reinforcement Learning, Unsupervised Learning and Supervised Learning.

Question 4

What is Artificial Intelligence?

Answer 4

The capability of a computer system to mimic human cognitive functions such as learning and problem solving.

Question 5

What is Machine Learning?

Answer 5

an application of AI that uses mathematical models of data to help a computer without direct instruction. This enables a computer system to continue learning and improving on its own, based on experience.

Question 6

What is Deep Learning?

Answer 6

Neural Network algorithms that learn important features in data by themselves. These network algorithms adapt through the process of repetitive training to uncover hidden patterns and new insights in complex data.

Question 7

What is an Alternative Definition to Machine Learning?

Answer 7

Machine Learning is the study of computer algorithms that improve automatically through experience according to a performance measure.

Question 8

Describe in Detail What Machine Learning Is?

Answer 8

Instead of writing a program by hand, we collect lots of examples that specify the correct output for a given input. A machine learning algorithm then takes these examples and produce a program that does the job.

Question 9

How does Machine Learning Work?

Answer 9

This program may look quite different to a typical hand-written program. It may contain millions of numbers (parameters). If we do it right, the program works for new cases (generalization) as well as the ones we trained it on.

Question 10

Why is Machine Learning Important (Part 1)?

Answer 10

1. Automation and Efficiency: Machines learn to perform tasks that would otherwise require human intervention.

Question 11

Why is Machine Learning Important (Part 2)?

Answer 11

2. Data Analysis and Prediction: From stock markets to weather forecasts, machine learning algorithms can process enormous amounts of data for analysis.

Question 12

Why is Machine Learning Important (Part 3)?

Answer 12

3. Personalization and Engagement: Imagine your smartphone understanding your needs and preferences.

Question 13

Why is Machine Learning Important (Part 4)?

Answer 13

4. Solving Complex Problems: In areas where traditional algorithms fail, machine learning thrives.

Question 14

Why is Machine Learning Important (Part 5)?

Answer 14

5. Social Impact: Addressing key challenges in sustainability, accessibility, and social justice.

Question 15

Pattern Recognition Tasks involving Machine Learning?

Answer 15

Facial Identities, Handwritten or spoken words, Medical Images.

Question 16

General Pattern Tasks involving Machine Learning?

Answer 16

Generating images (gap filling) or novel images for data generation.

Question 17

Anomaly Recognition Tasks involving Machine Learning?

Answer 17

Unusual sequences of credit card transactions, Unusual patterns of sensor readings in a nuclear power plant or unusual sound in your car engine.

Question 18

Prediction Tasks involving Machine Learning?

Answer 18

Future Stock Prices or Currency Exchange Rates.

Question 19

Another Example of a task that involves Machine Learning?

Answer 19

Recommendation systems for recommending user-specific content.

Question 20

Information Retrieval Tasks involving Machine Learning?

Answer 20

Developing automated systems for reading and parsing documents.

Question 21

Data Visualization Tasks involving Machine Learning?

Answer 21

Display data in a revealing way.

Question 22

Summarize Machine Learning?

Answer 22

Discuss the general field of Machine Learning, and where it sits in the grand scheme of things including Machine Learning and training models that generalize well to unseen data.

Question 23

State a Principle of Probability Theory?