Predictive Analytics: Identifying Network Attacks
Machine Learning
| Intermediate
- 18 videos | 2h 3m 34s
- Includes Assessment
- Earns a Badge
In cybersecurity, it's important to determine whether a user interaction or action represents an attack, followed by discerning the specific attack type and signature. Machine learning (ML) models and managed ML solutions like Microsoft Azure Machine Learning can help with this. In this course, learn how to create an Azure Machine Learning workspace, read in data, and categorize all of the different types of attacks. Next, discover how to train a random forest classification model using the scikit-learn library and test it on the in-sample validation data. Finally, practice performing multiclass classification to identify the specific type of attack. Upon completion, you'll be able to detect intrusions using data, train and evaluate classification models, and perform multiclass classification.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Create an azure machine learning workspace
Read in a network attack detection dataset to pandas
Create a column for the cyberattack type
View the training and testing datasets for identifying cyberattacks
Visualize network cyberattack data and view the unique values
Predict cyberattacks using heatmap and pie charts
Set up cyberattack data for machine learning (ml)
Perform one-hot encoding on cyberattack data and view the results -
View the performance of an overfit cyberattack prediction model
Predict cyberattacks by performing feature selection on a model
Use a chi-square test to perform feature selection
Set up data for cyberattack type classification
Train the attack type classification model and view the results on the in-sample validation data
Test the performance of an overfit attack classification model and select some features from the data
Perform feature selection for the cyberattack classification model
Select features for the model using the chi-square test
Summarize the key concepts covered in this course
IN THIS COURSE
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2m 3s
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4m 30s
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3. Importing Data on Network Cyberattacks7m 25s
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4. Creating a Data Column for Cyberattack Type7m 4s
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5. Viewing and Testing Network Cyberattack Data6m 12s
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6. Visualizing Network Cyberattack Data7m 54s
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7. Predicting Cyberattacks9m 6s
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8. Setting Up Cyberattack Data for Machine Learning5m 18s
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9. Performing One-hot Encoding on Cyberattack Data7m 45s
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10. Viewing Cyberattack Prediction Model Performance7m 35s
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11. Predicting Cyberattacks with Feature Selection7m 34s
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12. Using a Chi-square Test for Feature Selection7m 41s
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13. Setting Up Data for Cyberattack Type Classification7m 40s
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14. Training the Cyberattack Type Classification Model6m 2s
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15. Testing an Overfit Cyberattack Classification Model7m 26s
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16. Performing Classification Model Feature Selection8m 36s
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17. Selecting Features Using the Chi-square Test9m 41s
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18. Course Summary4m 3s
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