The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Automated ML for RNA Design with Danny Stoll - TWIML Talk #288
Aug 5, 2019
In this engaging discussion, Danny Stoll, a Research Assistant at the University of Freiburg specializing in automated machine learning for RNA design, reveals his team's innovative work in RNA design. He breaks down the design process through reverse engineering and how deep learning algorithms are applied for sequence training. Key topics include the synergy of machine learning and RNA functionality, challenges of hyperparameter optimization, and the integration of traditional and statistical methods for enhanced efficiency.
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Deep Learning Journey
- Danny Stoll's interest in math led him to machine learning and deep learning in high school.
- He started with Andrew NG's online course and got hooked.
Democratizing Machine Learning
- Automating machine learning makes it accessible to individuals without computer science backgrounds.
- This democratization of machine learning helps people integrate AI into products and research.
RNA Design's Importance
- RNA's spatial structure dictates its function and is linked to diseases like Parkinson's and Alzheimer's.
- RNA design aims to create RNA sequences that fold into specific structures to achieve desired functions.