Advanced AI: Deep Reinforcement Learning in Python
52 Lessons (5h)
- Introduction and Logistics
- Background Review
- OpenAI Gym and Basic Reinforcement Learning Techniques
- TD Lambda
- Policy Gradients
- Deep Q-Learning
The Complete Guide to Mastering AI Using Deep Learning & Neural Networks
The Lazy Programmer is a data scientist, big data engineer, and full stack software engineer. For his master's thesis he worked on brain-computer interfaces using machine learning. These assist non-verbal and non-mobile persons to communicate with their family and caregivers.
He has worked in online advertising and digital media as both a data scientist and big data engineer, and built various high-throughput web services around said data. He has created new big data pipelines using Hadoop/Pig/MapReduce, and created machine learning models to predict click-through rate, news feed recommender systems using linear regression, Bayesian Bandits, and collaborative filtering and validated the results using A/B testing.
He has taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Humber College, and The New School.
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