An introduction to Machine Learning with TensorFlow and Keras
TimeMonday, July 238:30am - 12pm
DescriptionThis class introduces participants to the basics of Machine Learning, specifically unsupervised, supervised and deep learning using the open-source TensorFlow framework and deep-learning framework Keras. Participants will gain a high-level understanding of the mathematical formulation behind the models. Due to the vastness of the topic under discussion, supplemental information will be available on the author's website, which will be updated at the end of the session to address topics that may arise during the course of the session but might be outside the scope of a 3hr workshop format.
For unsupervised learning, we will look at clustering and dimensionality reduction and implement both using the TensorFlow framework. For supervised learning, we will cover Decision Surfaces, Support Vector Machines, Linear Regression and Logistic Regression. Participants will be introduced to implementations of the above using TensorFlow. Users will also learn about the optimization algorithms popularly used in Machine Learning problems.
The final part of this workshop introduces the concepts of Deep Learning using the open-source tools TensorFlow and Keras. Users will learn how to model and train a Convolutional Neural Network for an image classification problem and a language modeling problem with Recurrent Neural Networks in TensorFlow. We will conclude by introducing Keras, a high-level framework for deep-learning problems and how the solution of the above problems can be simplified using the Keras API.