Quiz: Discovering ML use cases in day-to-day business

 1. You manage a website that provides users with personalized fashion and style advice. You do this through a machine learning model that is given a user’s style preferences, and the algorithm recommends clothing available from various websites. You receive a percentage of the sale if a customer decides to purchase the items. What are the benefits of personalization in machine learning in this use case

Answer: It allows the system to provide more valuable services and scalability.

2. You run a furniture store that accepts and sells used furniture. Until now, you have asked traders and employees to inspect the items and judge the condition of various parts. This information would be used to create a cost evaluation for the item. However, this business process is time consuming and laborious and is prone to oversights. How can you best use machine learning to automate the business processes in this scenario?

Answer: Train a machine learning model that can predict the cost of furniture based on specific photos.

3. You work in a large technology company that has decided to create an app which uses the cloud to provide users with photo and image storage. You want to use machine learning to add features to the app such as search capabilities, automatic filters, facial recognition, subject recognition, and automatic album creation. To create such an app with these features would require many machine learning models working together. Which machine learning models would you expect to be used to automatically curate an album named “Cooking From Home"?

Answer: Location detection and subject image recognition

4. You are the manager of a startup energy provider. You have a variety of unstructured and structured data from your customers that you want to organize, including correspondence emails, customer zip codes, phone numbers, average energy consumption information, and copies of letters sent to customers. How can unstructured data be defined?

Answer: Data that cannot be easily stored or queried in a relational database

5. Machine learning is becoming more affordable for businesses of all sizes. However, it can be tempting to use only one machine learning model in your business to save on costs, time, and maintenance. Why is it a good idea to divide a large machine learning use case into smaller use cases and then build separate models for each case?

Answer: Combining multiple small models is more powerful than using one model to do everything.