Course Schedule

26-Aug Class Introduction/Getting Started with Machine Learning Readings

  • Ch 1: “The Machine Learning Landscape”  in Géron, Aurélien. (2019). Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow’ O’Reilly Media, Inc. 3–31.
  • Ch 1: “Introduction” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 1–25.
2-Sept Asynch DataCamp Assignment 1 (Hands-on Data Pre-Processing):

  • Data Manipulation with pandas
  • Streamlined Data Ingestion with pandas
9-Sept Class Inspecting Data Readings

  • Ch 2: End-to-End Machine Learning Project. in Géron, Aurélien. (2019). Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow’ O’Reilly Media, Inc. 33–66.
15-Sept Data Camp Assignment 1 Due
16-Sept Class Representing Data Readings

  • Ch 4: “Representing Data/Engineering Features” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 213–55
30-Sept Class Evaluation Methods Readings

  • Ch 5: “Model Evaluation and Improvement” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 213–55
7-Oct Asynch DataCamp Assignment 2 (Hands-on Supervised Learning, Part 1):

  • Preprocessing for Machine Learning in Python
  • Supervised Learning with scikit-learn
15-Oct Data Camp Assignment 2 Due
21-Oct Class Supervised Learning (k-Nearest Neighbors)

Readings

  • Ch 2: “Supervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 27–70

Videos 

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28-Oct Class Supervised Learning (Linear Models)

Readings

  • Ch 2: “Supervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 27–70

Videos

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31-Oct Project 1 Due
4-Nov Async DataCamp Assignment 3 (Hands-on Supervised Learning, Part 2):

  • Linear Classifiers in Python
  • Machine Learning with Tree-Based Models in Python
11-Nov Class Supervised Learning (Naive Bayes Classifiers and Decision Trees, Support Vector Machines, and Uncertainty estimates from Classifiers)Readings

  • Ch 2: “Supervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 70–106 and 121–131

Videos 

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15-Nov Data Camp Assignment 3 Due
18-Nov Class Supervised Learning (Naive Bayes Classifiers and Decision Trees, Support Vector Machines, and Uncertainty estimates from Classifiers)Readings

  • Ch 2: “Supervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 70–106 and 121–131

Videos 

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25-Nov Class Unsupervised Learning (Dimensionality Reduction & Feature Extraction, and Manifold Learning)
Ethics (Part One)Readings

  • Ch 3: “Unsupervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 133–170
  • Bostrom, Nick, and Eliezer Yudkowsky. (2014). “The ethics of artificial intelligence.” The Cambridge Handbook of Artificial Intelligence. 316–34. https://nickbostrom.com/ethics/artificial-intelligence.pdf

Videos

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2-Dec Async DataCamp Assignment 4 (Hands-on Unsupervised Learning)

  • Unsupervised Learning in Python
  • Cluster Analysis in Python
30-Nov Project 2 Due
9-Dec Class Unsupervised Learning (Clustering)
Ethics (Part Two)Readings

Videos

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15-Dec Data Camp Assignment 4 Due
Project 3 Due
16-Dec Class Project Presentations
22-Dec Final Project Due