Labs
- Lab -- Github, Markdown, and You
- Lab -- Python for Data Science
- Lab -- Publicly Accessible Datasets
- Mini-Lab -- Downloading datasets with guards
- Mini-Lab -- Pickling Models
- Lab -- Flask Docker JSON API
- Lab -- Sklearn Pipelines with Stateless Transformers
- Lab -- Deploying an sklearn model to GCP Cloud Run
Pages
Mini Lessons
- Dealing with Unbalanced Datasets
- Scaling and Standardizing
- Netflow Outlier Detection (Anomaly Detection)
- scikit-learn pipeline model evaluation plots (ROC and PR-curve)
- Fetching infosec-related machine learning datasets with scikit-learn
Archived labs
- Lab -- AWS and GCP Machine Learning
- Lab -- Business Analytics Conceptual Competency
- Lab -- Deploying to Heroku
- Lab -- Job Market
- Lab -- A Flask app to run model predictions via JSON
- Lab -- Pickling ML Models
Syllabi Links
- MSBX5500 Spring 2022 class website
- MSBX5500 Spring 2021 class website
- MSBX5500 Spring 2020 class Github repo
- This cohort did an incident response flask app where you could upload pcaps to a mongodb, then run
argus / raagainst then to get netflows, which were fed against ML models (repo, project planning notes)
- This cohort did an incident response flask app where you could upload pcaps to a mongodb, then run