Professor Pieter Abbeel delivers his keynote on Deep Learning for Robotics, at NIPS 2017. Pieter Abbeel is a professor at UC Berkeley, EECS, BAIR,
Tag: Deep Learning
Deep Learning for Self-Driving Cars – Lecture 1 and 5
Deep Learning for Self-Driving Cars (2018 version) Lecture 1 and 5 Deep learning: Set of techniques that have worked well for AI techniques in
Deep learning based software defect prediction
The complexity of modern software systems is increasing, and the resulting software applications often contain defects that can have severe negative impacts on the
What Deep Learning Means for Artificial Intelligence: Jonathan Mugan
Jonathan Mugan, a computer science researcher specializing in Machine Learning and AI, gave a presentation titled “What Deep Learning Means for Artificial Intelligence”. AI
Deep Learning In 5 Minutes | What Is Deep Learning?
This video on “What is Deep Learning” provides a fun and simple introduction to its concepts. It was produced by Simplilearn. We learn about
Deep learning for lung Cancer detection and classification | Article
Lung cancer is one of the most important deadly diseases in the world. The recent estimates provided by the World Health Organization (WHO) says
Deep Learning at Booking.com: Emrah Tasli, Stas Girkin
Deep learning has been widely influential in academic research and also recently finding its way into the industry. This talk explains how we utilize
Predicting Academic Performance of Students from VLE Big Data using Deep Learning Models
Rapid advancements in Technology-Enhanced Learning platforms have shown a tremendous increase in online educational data to yield ample educational repositories – demonstrating a significant
The Rise of Artificial Intelligence through Deep Learning: Yoshua Bengio
A revolution in AI is occurring thanks to progress in deep learning. How far are we towards the goal of achieving human-level AI? What
Singularity of the Hessian in Deep Learning | Yann LeCun, Leon Bottou, Levent Sagun | Article
Given a (piece-wise) differentiable loss function, and a gradient-based algorithm to minimize it, the knowledge of the second-order information about it can tell us