IBM Watson AutoAI machine learning tutorial | Data exploration and visualization

IBM Watson AutoAI machine learning tutorial | Data exploration and visualization

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United States IBM Developer
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Published on ● Video Link: https://www.youtube.com/watch?v=knxbJgPmD5E


Duration: 8:12
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This is the first video in a three-part series from @Horea Porutiu.

Part 2: https://youtu.be/E_ArfAy3A4k
Part 3: https://youtu.be/su79BFQ9VU0
Watson Machine Learning web-app demo using AutoAI: https://youtu.be/B1WAOiO1o4o

Here, Horea explores the project architecture, the data set, and run visualizations on the data. We want to see if there is any strong feature that helps us predict insurance charges (expenses) in our data set. We see that smoking is a big predictor by running a boxplot on the smoking feature, and the feature we are trying to predict - charges (expenses). Lastly, we check if there is bias in the data by seeing if there are differences in the insurance expenses between males and females while keeping all other features constant.

For more, visit these links:
- Free IBM Cloud account needed, register here: https://tinyurl.com/y4mzxow5

- The data set: https://www.kaggle.com/noordeen/insurance-premium-prediction

- Project GitHub: https://github.com/IBM/predict-insurance-charges-with-ai

If you want to see more of Horea’s content, focused on open-source, blockchain, and artificial intelligence, see his channel at: https://www.youtube.com/channel/UCSQpzlNDZOUR3LAaGWNMovw

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#MachineLearning
#DataVisualization
#AutoAI



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