This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting).

WHAT YOU WILL LEARN

• Describe how machine learning is different than descriptive statistics.
• Create and evaluate data clusters.
• Explain different approaches for creating predictive models.
• Build features that meet analysis needs.

SKILLS YOU WILL GAIN

• Python Programming
• Machine Learning (ML) Algorithms
• Machine Learning
• Scikit-Learn