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Reinforcement Learning: Crash Course AI #9
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Reinforcement Learning: Crash Course AI #9
Reinforcement learning is particularly useful in situations where we want to train AIs to have certain skills we don’t fully understand ourselves. Unlike some of the techniques we’ve discussed so far, reinforcement learning generally only looks at how an AI performs a task AFTER it has completed it. And when an AI completes that task ...
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AI • Machine Learning • Tech on Instagram: "In most deep learning models, an input is transformed by passing it through a series of large matrices filled with tunable parameters. Each matrix represents a layer, and when your input reaches it, the model performs a bunch of math operations—mainly matrix multiplication, addition, and a nonlinear activation. In reality, deep learning models are simply layers and layers of math transformations and matrix multiplications applied to an input vector. Ea
1:25
AI • Machine Learning • Tech on Instagram: "In most deep learning models, an input is transformed by passing it through a series of large matrices filled with tunable parameters. Each matrix represents a layer, and when your input reaches it, the model performs a bunch of math operations—mainly matrix multiplication, addition, and a nonlinear activation. In reality, deep learning models are simply layers and layers of math transformations and matrix multiplications applied to an input vector. Ea
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