August 2019
Intermediate to advanced
342 pages
9h 35m
English
Content preview from Hands-On Artificial Intelligence for Cybersecurity
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Credit card fraud detection with IBM Watson Studio
Let's see the fraud detection predictive model that we loaded into the IBM Watson Studio Jupyter notebook (the complete code, released by IBM with the Apache 2.0 license, is available at the link: https://github.com/IBM/xgboost-smote-detect-fraud/blob/master/notebook/Fraud_Detection.ipynb ) in action.
The first operation to perform is to convert the credit card dataset, loaded in .csv format, into a pandas DataFrame;. This operation can be performed as follows.
Select the cell below Read the Data and convert it to the DataFrame section in the notebook and perform the following steps:
- Use Find and Add Data and its Files tab. You should see the file names that we uploaded earlier.
- Select ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.