• Welcome to Machine Learning
    Meet with Sebastian and Katie to discuss machine learning.

  • Naive Bayes - 9 hours remaining
    Learn about classification, training and testing, and run a naive Bayes classifier using Scikit Learn.

  • SVM - 6 hours remaining
    Build an intuition about how support vector machines (SVMs) work and implement one using scikit-learn.

  • Decision Trees - 5 hours remaining
    Learn about how the decision tree algorithm works, including the concepts of entropy and information gain.

  • Choose Your Own Algorithm - An hour remaining
    In this mini project, you will extend your toolbox of algorithms by choosing your own algorithm to classify terrain data, including k-nearest neighbors, AdaBoost, and random forests.

  • Datasets and Questions - 6 hours remaining
    Find out about the Enron data set used in the next lessons and mini-projects.

  • Regressions - 6 hours remaining
    See how we can model continuous data using linear regression.

  • Outliers - 4 hours remaining
    Sebastian discusses outlier detection and removal.

  • Clustering - 3 hours remaining
    Learn about what unsupervised learning is and find out how to use scikit-learn's k-means algorithm.

  • Feature Scaling - 2 hours remaining
    Learn about feature rescaling and find out which algorithms require feature rescaling before use.

  • Feature Selection - 4 hours remaining
    Katie discusses when and why to use feature selection, and provides some methods for doing this.

  • Text Learning - 7 hours remaining
    Find out how to use text data in your machine learning algorithm.

  • PCA - 6 hours remaining
    Learn about data dimensionality and reducing the number of dimensions with principal component analysis (PCA).

  • Validation - 3 hours remaining
    Learn more about testing, training, cross validation, and parameter grid searches in this lesson.

  • Evaluation Metrics - 3 hours remaining
    How do we know if our classifier is performing well? Katie discusses different evaluation metrics for classifiers in this lesson.

  • Tying It All Together - 10 minutes remaining
    Spend some time reflecting on the course material with Sebastian and Katie!

  • Final Project