Introduction to Machine Learning with Python and TensorFlow - This workshop will cover the basics of data science, from cleaning and preparing raw data with pandas, to visualizing different representations of data and relationships between attributes. We will cover the API behind scikit-learn and cover how to set up and run data transformation pipelines, then fit some machine learning models to the data. We will show you how to tune the model to get more accurate results and run cross-validation. In the second part of the session, we will explore how to build more complex models with TensorFlow, a multi-purpose library for linear algebra and tensor manipulation. Using the same APIs provided by scikit-learn, we'll introduce a simple neural network into our data processing pipeline and walk through training a neural net using tabular and image data.