Deep learning is everywhere now. Every time you do a Google search, you are using a trained deep learning model. Google CEO Sundar Pichai recently asserted that if the last decade was about ‘mobile-first’, then the next decade will be about ‘AI-first’. Within the larger artificial intelligence and machine learning domains, ‘deep learning’ is where many of the most significant innovations are occurring - self-driving cars, self-organizing drone swarms, computer vision, conversational interfaces, gene editing, emotion recognition, etc.,
Deep learning will impact nearly every industry on the planet, and there will be countless opportunities to take advantage of this technology. While most people who are aware of deep learning think of it as the domain of data scientists and mathematicians, it takes skilled software engineers to implement deep learning models as practical software in real-world systems.
This meetup aims to make deep learning accessible to anyone who has an interest in it - data scientists, software engineers, tech-savvy entrepreneurs, students, etc., Everyone is welcome, so come join us!
For more information, or to inquire about presenting or sponsoring, please email:
The Atlanta Deep Learning Meetup, in partnership with the Georgia Tech Advanced Technology Development Center (ATDC) (http://atdc.org) and other sponsors - including NVIDIA, eHire, and Lockheed Martin - has become the THE place in Atlanta to plug into the community surrounding this leading-edge data science technology. We welcome all participants, from deep learning experts to business people who are AI novices, and it's free to attend.
At our June meetup, Chris DeBellis presents an 'Introduction to Deep Reinforcement Learning'.
Reinforcement Learning is the set of algorithms used to teach autonomous systems how to obtain a specific goal. When combined with deep learning, these algorithms can achieve better than human performance on certain tasks, such as beating the best Go players in the world.
We will discuss the basic approaches in Reinforcement Learning and how this is differs from supervised learning. We will implement a simple Q-Learning algorithm and have it learn a simple task. We will discuss the limitations of this approach and the motivation for incorporating deep neural networks into reinforcement learning. Finally we will implement a deep neural network with Q-Learning (DQN) using an example from OpenAI Gym.
Come join us on Monday, June 10th at 6:30pm EDT at ATDC, in the Community Room on the 2nd floor of the Centergy Building. There is convenient parking in the adjacent Centergy Parking Deck (Google Maps).
Spend the evening expanding your AI horizons. We guarantee you will leave inspired.