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Jen Looper 4 years ago
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# Introduction to natural language processing # Introduction to natural language processing
This lesson covers a brief history and important concepts of *computational linguistics* focusing on *natural language processing*. This lesson covers a brief history and important concepts of *natural language processing*, a subfield of *computational linguistics*.
## [Pre-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/31/) ## [Pre-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/31/)

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# Introduction to Reinforcement Learning and Q-Learning # Introduction to Reinforcement Learning and Q-Learning
![Summary of reinforcement in machine learning in a sketchnote](../../sketchnotes/ml-reinforcement.png)
> Sketchnote by [Tomomi Imura](https://www.twitter.com/girlie_mac)
Reinforcement learning involves three important concepts: the agent, some states, and a set of actions per state. By executing an action in a specified state, the agent is scored with a reward. Again imagine the computer game Super Mario. You are Mario, you are in a game level, standing next to a cliff edge. Above you is a coin. You being Mario, in a game level, at a specific position ... that's your state. Moving one step to the right (an action) will take you over the edge, that would give you a low numerical score. However, pressing the jump button, you would score a point and you would be alive. That's a positive outcome and that should award you a positive numerical score. Reinforcement learning involves three important concepts: the agent, some states, and a set of actions per state. By executing an action in a specified state, the agent is scored with a reward. Again imagine the computer game Super Mario. You are Mario, you are in a game level, standing next to a cliff edge. Above you is a coin. You being Mario, in a game level, at a specific position ... that's your state. Moving one step to the right (an action) will take you over the edge, that would give you a low numerical score. However, pressing the jump button, you would score a point and you would be alive. That's a positive outcome and that should award you a positive numerical score.
The point of all this is that by using reinforcement learning and a simulator (the game), you can learn how to play the game to maximize the reward which is staying alive and scoring as many points as possible. The point of all this is that by using reinforcement learning and a simulator (the game), you can learn how to play the game to maximize the reward which is staying alive and scoring as many points as possible.

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- Take the post-lecture quiz - Take the post-lecture quiz
- Complete the challenge - Complete the challenge
- Complete the assignment - Complete the assignment
- After completing a lesson group, visit the [Discussion board](/discussions) and "learn out loud" by filling out the appropriate PAT rubric. A 'PAT' is a Progress Assignment Tool that is a rubric you fill out to further your learning. You can also react to other PATs so we can learn together. - After completing a lesson group, visit the [Discussion board](/discussions) and "learn out loud" by filling out the appropriate PAT rubric. A 'PAT' is a Progress Assessment Tool that is a rubric you fill out to further your learning. You can also react to other PATs so we can learn together.
> For further study, we recommend following these [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-15963-cxa) modules and learning paths. > For further study, we recommend following these [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-15963-cxa) modules and learning paths.

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