2020 Virtual Machine Learning Boot Camp
This virtual two-day boot camp will provide a broad introduction to Machine Learning (ML) from an executive perspective. Our goal is to give a manager or a CEO in a field such as medicine, finance, manufacturing, or energy an introduction to the essential concepts behind Machine Learning. Taught by a team of Rice professors in the computational sciences, the Machine Learning Boot Camp will integrate lectures describing the basic concepts to state-of-the-art Machine Learning.
By the end of the boot camp, participants will be familiar with the following topics:
- What is ML? What is it good for?
- Fundamentals of ML (training/testing/validation, loss functions, featurization, regularization), along with the basics of optimization.
- ML models: linear regression, logistic regression, kernel methods, support vector machines, clustering methods, dimensionality reduction techniques.
- Decision trees, random forests, ensemble methods, boosting and bagging.
- Fundamentals of Deep Learning: basic feedforward neural networks and the perceptron, optimization methods in neural networks and backpropagation, convolutional neural networks, autoencoders and variational autoencoders, recurrent neural networks and LSTMs, generative models and GANS.
- Reinforcement learning and its applications in deep learning.