Repository for course notes for the Analytics Class, Spring 2018. All documents are Jupyter notebooks. You can view the notes on the GitHub website, or via the nbviewer feature of the Jupyter web site (just click on the link below).
- Overview, Docker, Jupyter (1/22)
- Unsupervised learning
- PCA (1/24-1/29)
- Factor analysis (1/31)
- ICA (1/31)
- Clustering (2/5 - 2/7)
- Supervised learning
- Linear discriminat analysis (LDA) (2/12)
- Logistic regression (2/14)
- Support vector machine (SVM) (2/19 - 2/21)
- k nearest neighbors (kNN) (2/26)
- Decision trees (2/28 - 3/5)
- Cross validation (3/7)
- Network data analysis
- Network basics (3/26)
- Network metrics (3/28)
- Centrality measures (4/2 - 4/4)
- Newtork communities (4/9 - 4/11)
- Natural language processing
- Text processing (4/16 - 4/18)
- Corpora & WordNet (4/23)
- Word cloud (4/25)
- Text classification (4/30 - 5/2)
- Docker source: Python plus a number of analytics libraries including scikit-learn, networkx, NLTK (with the book corpus), and wordcloud. Also contains Graphviz.
- Docker image available from Docker hub
- Git & GitHub tutorial