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Principles of Autonomy Sp 25: L5 Neural Networks (Part 2) and Vision (Part 1)

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Neural networks, gradient explosion and implosion, implementation, pragmatics of training, bias and variance, over-under fitting

Introduction to vision and forward imaging model, intrinsic and extrinsic matrices, homogeneous coordinates.

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Principles of Autonomy Sp 25: L5 Neural Networks (Part 2) and Vision (Part 1)

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