Introduction to Deep Learning
The video recording of this talk can be viewed here. The short course materials are available at https://smi2021.scientistcafe.com/
Deep Learning is ubiquitous today across data-driven applications as diverse as machine vision, natural language processing, and super-human game-playing. This half-day workshop will introduce the fundamentals of the main types of deep learning models. You will also learn the motivation and use cases of deep learning through hands-on exercises using R and Python in the cloud environment. This workshop is designed for the audience with a statistics background. No software download or installation is needed, everything is done through an internet browser (Chrome or Firefox) in Databricks free cloud environment.
- Feedforward Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Deep Learning Hands-on (Python and R)
Instructor: Hui Lin, hui [at] linhui [dot] org
Bio: Hui Lin is currently a Quant Researcher at Google. Before Google, Hui held different roles in data science. She was the head of data science at Netlify, where she built and led the data science team, and a Data Scientist at DuPont, where she did a broad range of predictive analytics and market research analysis. She is the blogger of https://scientistcafe.com/ and the 2018 Program Chair of ASA Statistics in Marketing Section. She enjoys making analytics accessible to a broad audience and teaches tutorials and workshops for data science practitioners. She holds MS and Ph.D. in statistics from Iowa State University.