Ray Kurzweil, one of the world’s leading inventors, thinkers, and futurists, with a thirty-year track record of accurate predictions and called “the restless genius”
Lectures
Deep Learning Tutorial with Python & Machine Learning with Neural Networks | Udemy
In this video, Deep Learning Tutorial with Python | Machine Learning with Neural Networks Explained, Udemy instructor Frank Kane helps de-mystify the world of
CS230 Deep Learning Lectures | Stanford Engineering
Deep Learning is one of the most highly sought after skills in AI. In this course, you will learn the foundations of Deep Learning,
Does Artificial Intelligence Need More Innate Machinery?
Debate between Facebook’s head of Artificial Intelligence, Yann LeCun and Prof. Gary Marcus at New York University. The debate was moderated by Prof. David
Stanford CS224N: NLP with Deep Learning | Winter 2019
The field of natural language processing (NLP) is one of the most important and useful application areas of artificial intelligence. NLP is undergoing rapid
Stanford CS 330: Deep Multi-Task and Meta Learning
While deep learning has achieved remarkable success in supervised and reinforcement learning problems, such as image classification, speech recognition, and game-playing, these models are,
MIT 6.S191 Introduction to Deep Learning | New 2019 Edition
MIT’s introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of
CS234: Reinforcement Learning Lectures | Stanford Engineering | Winter 2019
To realize the dreams and impact of AI requires autonomous systems that learn to make good decisions. Reinforcement learning is one powerful paradigm for
Strong AI: Why We Should Be Concerned
Joscha Bach (AI researcher) who worked and published about cognitive architectures, mental representation, emotion, social modeling, and multi-agent system, is explaining the impact and
Advanced Deep Learning Course, by DeepMind
Advanced Deep Learning Course, by DeepMind Lecture 1 – Introduction to Machine Learning-Based Ai Lecture 2 – Introduction to Tensor Flow Lecture 3 –