First Deep Learning for coders MOOC launched by Jeremy Howard
Leading Data Scientist and entrepreneur Jeremy Howard launches a free Deep Learning course that shows end-to-end how to get state of the art results, including a top place in a Kaggle competition.
Jeremy P. Howard, @JeremyPHoward,
is a leading Machine Learning and Deep learning researcher and entrepreneur.
His current startup is fast.ai and he is also on faculty at USF and Singularity University.
Previously, he was CEO and founder of Enlitic, Kaggle President, and #1 ranked Kaggle competitor.
Jeremy initiatives attracts a lot of attention in the industry, so I was very interested to learn from him about his latest project, a first
Deep Learning for coders MOOC at course.fast.ai. The course is totally free and includes no advertising - Jeremy created it purely as a service to the community.
Deep Learning For Coders is a new online course that, for the first time, promises to teach coders how to create state of the art deep learning models. It covers all the practical details of real deep learning applications that are rarely shared outside of the 'inner circle'.
It contains 18 hours of lessons, and includes access to a vibrant deep learning community where many questions are asked and answered. Many new libraries and techniques are introduced for the first time, designed specifically to make it easier and faster to create world class deep learning models. The course also introduces new scripts that fully automate the creation of cloud-based deep learning development environments.
Jeremy says that this is
Jeremy initiatives attracts a lot of attention in the industry, so I was very interested to learn from him about his latest project, a first
Deep Learning for coders MOOC at course.fast.ai. The course is totally free and includes no advertising - Jeremy created it purely as a service to the community.
Deep Learning For Coders is a new online course that, for the first time, promises to teach coders how to create state of the art deep learning models. It covers all the practical details of real deep learning applications that are rarely shared outside of the 'inner circle'.
It contains 18 hours of lessons, and includes access to a vibrant deep learning community where many questions are asked and answered. Many new libraries and techniques are introduced for the first time, designed specifically to make it easier and faster to create world class deep learning models. The course also introduces new scripts that fully automate the creation of cloud-based deep learning development environments.
Jeremy says that this is
- First deep learning course to show end-to-end how to get state of the art results (including how to get a top place in a Kaggle competition)
- First code-centric full deep learning course (18 hours of lessons)
- First time that nearly every part of a convolutional neural net has been implemented as a spreadsheet!
- First release of new fast.ai libraries that dramatically simplify neural net best practices (especially transfer learning)
- First public availability of previously private, very active and helpful, deep learning community: forums.fast.ai
- First public release of scripts that fully automate creation of deep learning AWS instances, and of fast.ai's special deep learning AMI
