Developer · Lifetime deal
Advanced AI: Deep Reinforcement Learning in Python
This course is all about the application of deep learning and neural networks to reinforcement learning.
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Prices in USD, excluding tax.
| Advanced AI | |
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| Includes | Lifetime Access; Certification Included; 5 hours content; Web streaming; Mobile streaming; For all levels |
What is Advanced AI: Deep Reinforcement Learning in Python?
Description:
This course is all about the application of deep learning and neural networks to reinforcement learning. The combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level. Unlike supervised and unsupervised learning algorithms, reinforcement learning agents have an impetus—they want to reach a goal. In this course, you'll work with more complex environments, specifically, those provided by the OpenAI Gym.
- Access 52 lectures & 5 hours of content 24/7 - Extend your knowledge of temporal difference learning by looking at the TD Lambda algorithm - Explore a special type of neural network called the RBF network - Look at the policy gradient method - Examine Deep Q-Learning
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.
Multiple businesses have benefitted from his web programming expertise. He does all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies he has used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases he has used MySQL, Postgres, Redis, MongoDB, and more.
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Is this course still available?
The lifetime deal sold through StackSocial is archived and no longer available. The course itself is still sold by The Lazy Programmer on Udemy and deeplearningcourses.com, so the content remains accessible through those channels.
What did this course cover?
The course covered advanced deep reinforcement learning in Python, including temporal difference learning, the TD Lambda algorithm, RBF networks, the policy gradient method, Deep Q-Learning (DQN), and A3C. Students worked with OpenAI Gym environments including Atari games.
Who is this course best suited for?
Learners who already have foundational knowledge of reinforcement learning and Python and want to move into advanced deep learning approaches. It is a sequel to The Lazy Programmer's introductory RL course, so prior knowledge of Q-learning and Markov decision processes is expected.
Who is The Lazy Programmer?
The Lazy Programmer is a data scientist and full-stack engineer whose master's thesis involved brain-computer interfaces using machine learning. He has taught data science and ML at universities including Columbia University and NYU, and has built ML systems in digital advertising.
How long is the course?
The course includes 52 lectures and approximately 5 hours of video content.
What real-world applications did the course reference?
The course referenced AlphaGo defeating a world Go champion, self-driving car perception, and machines playing Atari video games at superhuman level — all outcomes of combining deep learning with reinforcement learning.
Where can I take a similar course today?
The Lazy Programmer's full reinforcement learning catalogue is available on Udemy and at deeplearningcourses.com. DeepMind's course on RL and the Hugging Face Deep RL Course are also strong free alternatives.
Often compared with
These are other tools in the same space, not deals on GrabLTD.
- Udemy (Lazy Programmer catalogue)
- Coursera Deep Learning Specialization
- Hugging Face Deep RL Course
- fast.ai Practical Deep Learning
