Quiz and summary
Contents
1.7. Quiz and summary¶
1.7.1. Quiz 1¶
Complete Quiz 1 to check your understanding of this topic. You are advised to score at least 50% to proceed to the next topic.
1.7.2. Summary¶
Machine learning automates the process of learning a model from data that captures hidden patterns or relationship to help us make intelligent, data-driven predictions or decisions. It has been proven to be very useful in many applications, such as image recognition, speech recognition, natural language processing, and many more. Understanding and applying machine learning through this course will help you to acquire essential skills for solving many real-world problems.
In this topic, you learnt:
Machine learning learns a model from data to make predictions or decisions.
The software-development life cycle of a machine learning project.
The meaning and importance of transparency in machine learning.
What a \(K\)-nearest neighbour (\(K\)-NN) classifier is and how to use it.
Next, we are delving into a fundamental statistical machine learning technique, Linear Regression!
1.7.3. References and further reading¶
This material is based on the following resources:
Ostmann F, Dorobantu C., AI in Financial Services, Alan Turing Institute, 2021. [Ostmann and Dorobantu, 2021]