In the last decade, deep learning has seen many innovations in terms of better neural network architectures, optimized hardware such as GPUs, TPUs which has made it possible to apply it in real-time applications that require low latency. This has indeed made the dream of self-driving cars or autonomous vehicles possible. Driving a car requires human-level intelligence which can be simulated using deep learning-based software. The applications include real-time Object recognition, Lane detection, Depth perception, 3D world mapping, Scene Understanding, Free space detection, etc which we will discuss in detail.

Why attend and Learning outcomes

1. Understand the relevant skills required getting a job in the autonomous sector

2. Will help the participants get started with the development process

3. Hiring the right candidates with the right skills for your company

4. Consultancy on the autonomous services

5. Understand the role of Deep Learning in autonomous sectors

6. How SDC functions

Instructor's Bio

Birupakshya Mahapatra, ML Engineer at

Birupakshya Mahapatra (aka Veer) is a Machine Learning engineer who has worked on multiple projects which include Deep Learning, Reinforcement Learning, NLP, Predictive Modelling. He is a very passionate individual who works as a mentor, ML consultant, and an AI evangelist in the industry. He has worked on applying various deep learning techniques in a self-driving car. From being a business consultant to becoming a Lead in Machine Learning he had worked in diversified roles and currently, he is associated with a start-up working on bringing AI to help humanity.

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    Applications of Deep Learning in self-driving cars

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