1 2 3 # Initialize Otter import otter grader = otter.Notebook("lab14.ipynb") Ungraded Lab 14: Clustering In this lab you will explore K-Means, Agglomerative Clustering, and Spectral Clustering. Spectral Clustering is out of scope for Spring 2022.ref. Note: This is an ungraded assignment. There is no Gradescope submission for this assignment. As this is a bonus and ungraded assignment, there will also be more limited staff office hours devoted to this ungraded homework.

1 2 3 # Initialize Otter import otter grader = otter.Notebook("lab11.ipynb") Lab 11: Principal Component Analysis In this lab assignment, we will walk through two examples that use Principal Component Analysis (PCA): one involving a dataset of iris plants, and another involving an artificial “surfboard” 3D dataset. 1 2 3 4 5 6 7 8 9 10 11 12 # Run this cell to set up your notebook from sklearn.

1 2 3 # Initialize Otter import otter grader = otter.Notebook("lab12.ipynb") Lab 12: Logistic Regression 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 # Run this cell to set up your notebook import numpy as np import pandas as pd import sklearn import sklearn.datasets import matplotlib.pyplot as plt import seaborn as sns import plotly.offline as py import plotly.graph_objs as go import plotly.