* Translate 1.1 (Intro to ML) to Korean
* Translate 1.2 (History of ML) to Korean
* Translate 1.3 (Fairness) to Korean
* Translate 1.4 (Techniques of ML) to Korean
* Translate 2.1 (Tools) to Korean
* Translate 2.2 (Data) to Korean
* Translate 2.3 (Linear) to Korean
* Translate 2.4 (Logistic) to Korean
* Translate 3.1 (Web App) to Korean
* Translate 4.1 (Intro to Classification) to Korean
* Translate 4.2 (Classifiers 1) to Korean
* Translate 4.3 (Classifiers 2) to Korean
* Translate assignment 4.4 (Applied) to Korean
* Translate assignment 5.1 (Visualize) to Korean
* Translate assignment 5.2 (K-Means) to Korean
* Translate assignment 6.1 (Intro to NLP) to Korean
* Translate assignment 6.2 (Tasks) to Korean
* Fix minor typo in assignment 6.2 (Tasks) Korean translation
* Translate assignment 6.3 (Translation Sentiment) to Korean
* Translate assignment 6.4 (Hotel Reviews 1) to Korean
* Translate assignment 6.5 (Hotel Reviews 2) to Korean
* Translate assignment 7.1 (Intro to Time Series) to Korean
* Remove English title from assignment 7.1 (Intro to Time Series) in Korean
* Translate assignment 7.2 (ARIMA) to Korean
* Translate 8.1 (Q-Learning) to Korean
* Translate assignment 8.2 (Gym) to Korean
* Translate assignment 9.1 (Applications) to Korean
Postscript: Real world applications of classic machine learning
In this section of the curriculum, you will be introduced to some real-world applications of classical ML. We have scoured the internet to find whitepapers and articles about applications that have used these strategies, avoiding neural networks, deep learning and AI as much as possible. Learn about how ML is used in business systems, ecological applications, finance, arts and culture, and more.
Ian Park
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