Lectures: You can obtain all the lecture slides at any point by cloning 2015, and using
git pull as the weeks go on.
Videos: You can see the entire list of videos here. Below we list them by class/section along with a link to the slides.
We’ve also started a YouTube channel for cs109. This channel has smaller videos dealing with nitty gritty stuff on the course.
Labs/Sections: Note that the Lab video and notebook is actually recorded and produced on the Thursday and Friday of the previous week, but is listed under the week that sections pertaining to the material on the Lab are given.
Week 1 (Mon Aug 31 - Fri Sep 4)
Week 2 (Mon Sep 7 - Fri Sep 11)
- Lab 1: Pandas, Python, and Github
- Lecture 2:
- Lecture 3: Exploratory Data Analysis
Week 3 (Mon Sep 14 - Fri Sep 18)
- Lab 2: Scraping, Pandas, Python, and viz
- Lecture 4: Pandas, SQL, and the Grammar of Data
- Lecture 5: Statistical Models
Week 4 (Mon Sep 21 - Fri Sep 25)
- Lab 3: Probability, Distributions, and Frequentist Statistics
- Lecture 6: Story Telling and Effective Communication
- Lecture 7: Bias and Regression
Week 5 (Mon Sep 28 - Fri 2 Oct)
- Lab 4: Regression, Logistic Regression: in sklearn and statsmodels
- Lecture 8: More Regression
- Lecture 9: Classification. kNN. Cross Validation. Dimensionality Reduction. PCA. MDS.
Week 6 (Mon Oct 5 - Fri 9 Oct)
- Lab 5: Machine Learning
- Lecture 10: SVM, Evaluation.
- Lecture 11: Decision Trees and Random Forests
Week 7 (Mon Oct 12 - Fri 16 Oct)
- Lab 6: Machine Learning 2
- Lecture 12: Ensemble Methods.
- Lecture 13: Best Practices
Week 8 (Mon Oct 19 - Fri 23 Oct)
- Lab 7: Ensembles
- Lecture 14: Best Practices, Recommendations and MapReduce.
- Lecture 15: MapReduce Combiners and Spark
Week 9 (Mon Oct 26 - Fri 30 Oct)
- Lab 8: Vagrant and VirtualBox, AWS, and Spark
- Lecture 16: Bayes Theorem and Bayesian Methods
- Lecture 17: Bayesian Methods Continued
Week 10 (Mon Nov 2 - Fri 6 Nov)
- Lab 9: Bayes
- Lecture 18: Bayesian Methods Continued,Text Data
- Lecture BONUS: Interactive Visualization
Week 11 (Mon Nov 9 - Fri 13 Nov)
- Lab 10: Text and Clustering
- Lecture 19: Clustering
- Lecture 20: Effective Presentations
Week 12 (Mon Nov 16 - Fri 20 Nov)
- Lab 10: Projects, and an example
- Repository: 2015Lab11
- Lecture 21: Experimental Design
- Lecture 22: Deep Networks