Ornella Altunyan
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README.md
Machine Learning in the Real World
In this curriculum, you have learned many ways to prepare data for training and create machine learning models. You built a series of classic Regression, Clustering, Classification, Natural Language Processing, and Time Series models. Congratulations! Now, you might be wondering what it's all for...what are the real world applications for these models?
While a lot of interest in industry has been garnered by AI, which usually leverages Deep Learning, there are still valuable applications for classical machine learning models, some of which you use today, although you might not be aware of it. In this lesson, you'll explore how ten different industries and subject-matter domains use these types of models to make their applications more performant, reliable, intelligent, and thus more valuable to users.
Pre-lecture quiz
Finance
One of the major consumers of classical machine learning models is the finance industry.
Credit card fraud detection
We learned about k-means clustering earlier in the course, but how can it be used to solve problems related to credit card fraud?
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.680.1195&rep=rep1&type=pdf
Wealth management
Education
Predicting student behavior
Preventing plagiarism
Course recommendations
Retail
Personalizing the customer journey
Inventory management
Health Care
Optimizing drug delivery
Hospital re-entry management
Disease management
Ecology and Green Tech
Forest management
Motion sensing of animals
Energy Management
This article discusses in detail how clustering and time series forecasting help predict future energy use in Ireland, based off of smart metering: https://www-cdn.knime.com/sites/default/files/inline-images/knime_bigdata_energy_timeseries_whitepaper.pdf
Insurance
Actuarial tasks
Consumer Electronics
Motion sensing
Software
UI regression
Document search
Recommendation engines
Arts, Culture, and Literature
Fake news detection
Classifying artifacts
Marketing
'Ad words'
Customer segmentation
✅ Knowledge Check - use this moment to stretch students' knowledge with open questions
🚀Challenge
Add a challenge for students to work on collaboratively in class to enhance the project
Post-lecture quiz
Review & Self Study
Assignment: Assignment Name