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This contains what I've learned about TensorFlow
basic-tensorflow's Introduction
- Basic concept about tensors (Dimension, Shape, Data Type)
- Casting method with tensors
- Methods to create special tensors (Eye, Ones, One_like, Zeros, Fill)
- Normal & Uniform distribution
- The conceot to implement indexing in tensors from different dimensions
- Simple calculating operation methods
- The concept of broadcasting
- Useful methods (Abs, Maximum, Minimum, Argmax, Argmin, Equal, Pow)
- Other methods (Reduce_sum, Reduce_mean, Sigmoid, Top_k)
- Multiply Matrix (Matmul)
- Transpose tensor (Transpose)
- Band_part method
- Inverse matrix (Inv)
- Singular value decompositions (Svd)
- Einsum Method
- Expand Dimensions Method (Expand_dims)
- Squeeze Method
- Reshape Method
- Concatenate Method (Concat)
- Stack Method
- Pad Method
- Gather Method
- Gather N-Dimensions Method (Gather_nd)
- Definition
- Boolean Mask Method (Boolean_mask)
- From Row Lengths Method (From_row_lengths)
- From Row Limits Method (From_row_limits)
- From Row Splits Method (From_row_splits)
- From Tensor Method (From_tensor)
- Definition
- To Dense Method (To_dense)
- Definition
- Join Method
- Length Method
- Definition
- Assign Sub Method (Assign_sub)
- Assign Add Method (Assign_add)
- Device Method
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