Get into Autonomous Vehicle 2.0 by learning Advanced Deep Learning
TOP COURSES
HYDRANETS
NEURAL OPTIMIZATION
END-TO-END REVOLUTION
Train yourself on the AV 2.0 Revolution
Autonomous Driving is evolving faster than you can catchup. One year, the revolution is Chat-GPT, the next one, everybody's already taken the idea into Foundation Models and End-To-End Learning.Â
If you'd like to stay up to date, there are 4 or 5 core ideas to understand:
- Transformers:Â and in particular Vision Transformers
- Self-Supervised Learning:Â How to train on "the entire internet" without supervision
- HydraNets: Multi-Task Learning techniques creating the new Foundation Models
- Bird-Eye View/Occupancy: The core vision tasks
- End-To-End Learning: The core approach used in today's revolution, using a single network from sensors to output trajectoryÂ
Advanced Deep Learning Courses
TRANSFORMERS
Still lagging behind on Transformers? This is because most examples out there are designed with language examples in mind. If you're a Computer Vision Engineer, you need image examples, what this course provides.
SELF-SUPERVISED LEARNING
How do companies possibly train models on the entire internet, without any labels? They use self-supervised learning. When you enter the Dojo, you'll learn exactly how, and build your own SSL pipelines.
HYDRANETS
Ever heard of HydraNets? These are architectures coming straight from Tesla that has the power to do multiple tasks at once. The entire AV 2.0 stack starts from this single technique.
NEURAL OPTIMIZATION
Are your neural networks consuming all memory and running at 5 FPS? This is because you haven't optimized them? In production, DL engineers use advanced approaches to deploy models, we'll learn them here.
BIRD-EYE-VIEW
Bird Eye View is THE skill to master nowadays. Every single vision based autonomous driving startup is using it, and this directly "feeds" end-to-end learning models.
END-TO-EnD REVOLUTION
A revolution is happening. End-To-End Learning has emerged, and hundreds of startups are converting to use learned approaches directly. This is an extremely advanced course, be cautious.
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Deep Learning State-of-The-Art
THE 4 CORE TOPICS I WOULD FOCUS ON IF I WANTED TO BE A LIDAR PERCEPTION ENGINEER IN 2025The 2024 Webinar on Deep Learning State Of The Art - Presented to Mercedes-Benz R&D
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