Volunteers
| Name | ML Category |
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| Jahanvi | Supervised |
| Akanksha | Unsupervised |
| Kanak Raj | Reinforced |
Supervised
Algorithms
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Un-supervised
Algorithms
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Reinforcement Learning
- Active Learning
- No labeled data
- Can afford to make mistakes?
- Is it possible to use a simulated environment for the task?
- Lots of time
- Think about the variables that can define the state of the environment.
- State Variables and Quantify them
- The agent has access to these variables at every time step
- Concrete Reward Function and Compute Reward after action
- Define Policy Function
Algorithms
| Name | Comments on Applicability | Reference |
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Q Learning |
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