People usually don’t mean supervised and unsupervised Machine Learning, when they talk about Artificial Intelligence. These kind of tasks are pretty trivial as compared to what we think of AIs doing like playing chess and Go, driving cars, and beating video games at a superhuman level. Recently, Reinforcement Learning has become popular for doing all of that and more.
Like Deep Learning, the theory was found in the 70s and 80s but it hasn’t been until not very long ago that we’ve been able to notice first hand the amazing results that are possible.
In 2016 we saw Google’s AlphaGo beat the world Champion in Go and AIs( Artificial Intelligence) are playing video games such as Doom and Super Mario. Moreover, self-driving cars have began driving on real roads with other drivers and even carrying passengers (Uber), all without human help. So, brace yourself for the future because the law of accelerating returns dictates that this progress is only going to continue to increase exponentially if you think it sounds amazing.
To learn about supervised and unsupervised Machine Learning is no small feat. There are more than 16 courses just on those topics alone and reinforcement learning yet opens up a whole new world. In this course, you will learn how the Reinforcement Learning paradigm is more different from supervised and unsupervised learning than they are from each other.
Moreover, there are many analogous processes you will learn here when it comes to teaching an agent and teaching an animal or even a human. It is very close thing that we have so far to a true General Artificial Intelligence.
You will learn from this course?
- How to solve problem like the multi-armed bandit and the explore-exploit dilemma
- How to calculate means and moving averages and their relationship to stochastic gradient descent
- Markov Decision Processes (MDPs), Dynamic Programming and Monte Carlo
- Temporal Difference (TD) Learning and Approximation Methods (i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm)
If you need more details about this course, visit here->->Artificial Intelligence- Reinforcement Learning in Python