Trained in Mathematics and Statistics, Helen is a data scientist and machine learning researcher with a passion for security, machine learning, and free and open source technology. Helen has worked on exciting projects in management consulting, technology start-ups, and non-profits in Asia, North America, and Europe. Helen has also taught mathematics, coding, writing, and astronomy to different audiences. When not writing code, building things, or sharing knowledge, she enjoys learning new spoken languages, photography, and long-distance running. She has many stories to tell, and you are welcome to ask her in person :)
Proposals for this user
As a major benchmark and trend-setter in machine learning and statistics, R, a free and open source statistical computing language, has much to offer to anyone interested in machine learning, statistics, or numerical computing. In this tutorial, I will share with the audience the vast ecosystem around R, and get the listeners started right away with some of the most widely used machine learning algorithms. You don't have to be a statistician or computer scientist to use R - its concise syntax and expressive nature will only make you want to use it more and more for machine learning and other computing tasks!
|Theory||2016-04-21 06:58:47 +0000|
Despite all the attention and buzz, Machine learning(ML) is woefully overlooked in the community of free and open source technology. In this presentation, I will examine the still prevalent proprietary legacy of ML, introduce the current open source stack of ML development and applications, and evaluate new proprietary attempts entering ML. Then, I will share with you the strategy recipes that we may need, in a battle to keep the booming field of ML free and open source.
|Culture||2016-04-14 06:53:01 +0000|