MacbookでTensorFlowでAIを使ってみよう、という企画です
1. TensorFlowのGettingStartedを読む
- Getting Started With TensorFlowを読んで基本を理解します
Tensor
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The central unit of data in TensorFlow is the tensor.
- TensorFlow内でのデータの基本的なユニットはtensor。
- A tensor consists of a set of primitive values shaped into an array of any number of dimensions.
- tensorは任意のN次元の配列に整形されたプリミティブ値のセットで構成される
- A tensor's rank is its number of dimensions.
- tensorのrankは次元数を表す
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3 # a rank 0 tensor; this is a scalar with shape []
- 3はrank0のtensor。[]の形のスカラー。
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[1. ,2., 3.] # a rank 1 tensor; this is a vector with shape [3]
- [1.,2.,3.]はrank1のtensor。[3]の形のベクター。
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[[1., 2., 3.], [4., 5., 6.]] # a rank 2 tensor; a matrix with shape [2, 3]
- [[1., 2., 3.], [4., 5., 6.]]はrank2のtensor。[2,3]の形の行列。
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[[[1., 2., 3.]], [[7., 8., 9.]]] # a rank 3 tensor with shape [2, 1, 3]
- [[[1., 2., 3.]], [[7., 8., 9.]]]はrank3のtensor。[2,1,3]の形。
TensorFlow Core tutorial
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A computational graph is a series of TensorFlow operations arranged into a graph of nodes.
- 計算グラフとは、一連のTensorFlow操作をノードのグラフに配置したもの
- Each node takes zero or more tensors as inputs and produces a tensor as an output.
- 各ノードは、0以上のtensorを入力として受取り、一つのtensorを出力する