31-May
Synch |
Introduction/What is 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.
- Jordan, Michael I. and Tom M. Mitchell. (2015). “Machine Learning: Trends, perspectives, and prospects” Science 349, 255—-60. http://www-cgi.cs.cmu.edu/~tom/pubs/Science-ML-2015.pdf
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1-June
Synch |
Getting Started with Machine Learning
Readings
- Ch 1: “Introduction” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 1–25.
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2-June
Synch |
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.
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6-June
Synch |
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
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7-June
Asynch |
DataCamp Modules:
- Introduction to Python course (If Needed)
- “Introduction to AI” from AI Fundamentals course
- Data Manipulation with pandas
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- Transforming Data
- Aggregating Data
- Slicing and Indexing
- Creating and Visualizing DataFrames (Optional)
- Writing Efficient Code with pandas (Optional)
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8-June
Synch |
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
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9-June
Async |
DataCamp Modules
- Cleaning Data in Python
- Common data problems
- Text and categorical data problems
- Advanced data problems
- Record linkage (optional)
- Preprocessing for Machine Learning in Python course
- Model Validation in Python course
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13-June
Synch |
Supervised Learning (k-Nearest Neighbors and 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
password is course number (no spaces) |
14-June
Asynch |
DataCamp Modules
- “Basic Modeling in scikit-learn (through Feature Importances)” (In Model Validation in Python course)
- “Classification” (in Supervised Learning with scikit-learn course)
- “Regression” (in Supervised Learning with scikit-learn course)
- “Cross Validation” (In Model Validation in Python course)
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15-June
Synch |
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
password is course number (no spaces) |
16-June
Asynch |
DataCamp Modules
- “Classification and Regression Trees” (in Machine Learning with Tree-Based Models in Python course)
- Linear Classifiers in Python course
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21-June
Synch |
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. http://faculty.smcm.edu/acjamieson/s13/artificialintelligence.pdf
Videos
password is course number (no spaces) |
22-June
Synch |
Unsupervised Learning (Clustering)
Ethics (Part Two)
Readings
- Ch 3: “Unsupervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 170–211
- West, Sarah Myers, Meredith Whittaker, and Kate Crawford. (2019). “Discriminating systems: Gender, race and power in AI.” AI Now Institute, 1–33. https://ainowinstitute.org/discriminatingsystems.pdf
Videos
password is course number (no spaces) |
23-June
Asynch |
DataCamp Modules
- Unsupervised Learning in Python course
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