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CI
#33:
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Add initial README for Tensor Engine project
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#32:
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feat(autograd): add sum(), Value::matmul backward, linear regression …
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#31:
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feat(autograd): add Value::matmul with AVX2 kernel forward + backward…
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#30:
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feat(autograd): migrate Value to Tensor<f64> backend, tensor ops, exa…
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#29:
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refactor(core): clippy erros
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#28:
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refactor(core): remove const generics from Tensor/TensorLayout to use…
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feat(autograd): add sine wave regression example, demonstrates scalar…
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fix(autograd): resolve clippy warnings - idiomatic iterators, allow s…
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miri validation fix
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feat(autograd): add Adam optimizer with gradient clipping, XOR conver…
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feat(autograd): add tanh, Activation enum, XOR training example
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feat(autograd): implement MLP with Neuron, Layer, forward pass, MSE l…
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#21:
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feat(autograd): add sub, pow with backward
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fix(autograd): fix Rc cycle with Weak
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#19:
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feat(autograd): implement Value with add, mul, relu, backward traversal
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feat(core): clean Tensor API - direct slice/get, Display truncation, …
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feat(macros): implement tensor! macro for tensor creation
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#16:
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feat(core): Add Display(5x5) option for Tensor
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Benchmark(Doc): Updated benchmark results and comparision
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Doc(benchmark):Current benchmark Result Against ndarray
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fix(core): add Default impls and remove needless return statements
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#12:
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feat(core):Vector based Tensor Layout
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feat(core): benchmark MaybeUninit layout against ndarray 64x64
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feat(core):Vector based Tensor Layout
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