AutoML Towards Deep Learning: Optimizing Neural Architectures and Hyperparameters
Offered By: Toronto Machine Learning Series (TMLS) via YouTube
Course Description
Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the future of deep learning and automated machine learning in this 57-minute conference talk by Professor Frank Hutter at the Toronto Machine Learning Series. Delve into the potential of AutoML to revolutionize deep learning systems by automating the optimization of neural architectures and hyperparameters. Learn about advances in joint optimization of meta-choices in deep learning pipelines, efficiency improvements in meta-optimization, and techniques for optimizing uncertainty estimates and robustness to data shift. Gain insights into how next-generation deep learning systems may provide a streamlined interface between domain experts and machine learning algorithms, potentially transforming the field of artificial intelligence.
Syllabus
AutoML Towards Deep Learning
Taught by
Toronto Machine Learning Series (TMLS)
Related Courses
Automated Machine Learning en Microsoft Power BICoursera Project Network via Coursera Automated Machine Learning en Power BI Clasificación
Coursera Project Network via Coursera AutoML con AutoSklearn y Google Colab
Coursera Project Network via Coursera Launching into Machine Learning
Google via Google Cloud Skills Boost Exam Tips: Designing and Implementing a Data Science Solution on Azure (DP-100)
LinkedIn Learning