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You want to create a machine learning algorithm to identify food recipes on the web. To do this, you create an algorithm that looks at different conditional probabilities. So if the post includes the word flour, it has a slightly stronger probability of being a recipe. If it contains both flour and sugar, it even more likely a recipe. What type of algorithm are you using?

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What is lazy learning?

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What is Q-learning reinforcement learning?

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Data in your model has low bias and low variance. How would you expect the data points to be grouped together on the diagram?

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