Machine Learning Foundations: A Case Study Approach

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The above projects have been done extensively using GraphLab Create machine learning framework. Inorder to run these in your personal systems, please go to https://dato.com/products/create/ and register yourself for a free trial. After downloading Graphlab Create, start the ipython notebook terminal by clicking Dato Launcher from your desktop.

Learning Outcomes:

1. Identify potential applications of machine learning in practice.
2. Describe the core differences in analyses enabled by regression, classification, and clustering.
3. Select the appropriate machine learning task for a potential application.
4. Apply regression, classification, clustering, retrieval, recommender systems, and deep learning.
5. Represent your data as features to serve as input to machine learning models.
6. Assess the model quality in terms of relevant error metrics for each task.
7. Utilize a dataset to fit a model to analyze new data.
8. Build an end-to-end application that uses machine learning at its core.
9. Implement these techniques in Python.