Training the model is just one part of shipping a deep learning project. This course teaches full stack production deep learning:
Students will work on deploying a deep learning system into production, learn how to prepare for interviews, and test their knowledge via an optional written exam. The FSDL community also offers benefits of an active peer network comprising top deep learning practitioners - learn, deploy, and collaborate with the best.
Co-Founder, President, and Chief Scientist of Covariant.AI, Professor at UC Berkeley
Co-Founder of Gradescope, Head of AI for STEM at Turnitin
Research Scientist at OpenAI
FSDL provides practical advice from expert speakers on getting models into production and offers great tips on how to serve these models in reliable and maintainable ways.- Jeremy Jordan, ML @ Proofpoint
It was a fabulous 3 days of deep learning Nirvana at the bootcamp. Both the content and the people in attendance were amazing.- Ram Iyer
Besides deep learning literature, this course also covers practical topics like trade offs between cloud and on prem GPU servers, how to hire and build an ML team, etc. Highly recommended!- Zellux Wang, ML @ Ike Autonomous Trucking
Fantastic workshop - great instructors/speakers, and solid content!- Jonathan Buck, AI @ AWS
A primary benefit for me was review of compute and tools (experiment management, etc) around ML. A large amount of ML is really infrastructure (managing labels, scaling compute, running metrics and experiments) - and this course had a nice treatment of these practical topics!- Lance Martin, Ike Autonomous Trucking
We strongly encourage members of underrepresented groups to apply. is generously sponsoring a scholarship program - details are available in the application.
Our course is aimed at people who already know the basics and want experience with the full stack. We expect you to have:
We will not review the fundamentals of deep learning (gradient descent, backpropagation, convolutional neural networks, recurrent neural networks, etc), so you should review these materials in advance of the bootcamp if you are rusty.
Over the course of the two days, the instructors will present material on setting up ML projects, debugging neural networks, data collection and management, infrastructure and tooling, testing and deployment, the ML job market, and the state of cutting-edge ML research. Participants will hear lectures from top industry practitioners and spend 30% of the time on labs, developings and deploying a deep learning system.
Below is the draft schedule for the bootcamp.
|8:30||Intro||Training & debugging|
|9:00||Setting up ML Projects|
|10:30||Labs 1/2/3||Labs 6/7|
|13:00||Infrastructure & tooling||Testing & deployment|
|14:30||Labs 4/5||Lab 8|
|16:00||Data management||Research areas|
|17:00||ML Hiring and Jobs|
|17:30||Guest lectures||Guest lectures|
|19:00||Happy hour||Happy hour|
We offer a discount off the professional price to current undergraduate and graduate students. Additionally, Turnitin is sponsoring a scholarship program for members of underrepresented groups. See the application for details.
For those unable to attend, materials from our last bootcamp can be found here.