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batch size 2

3D Tensor(Typical Natural Language Processing)

Step 1. Devide the sentences into words. 2. Vectorize each words. 3. Set up the batch size. Let's say here is data. [[나는 사과를 좋아해], [나는 바나나를 좋아해], [나는 사과를 싫어해], [나는 바나나를 싫어해]] 1. Devide the sentences into words. [['나는', '사과를', '좋아해'], ['나는', '바나나를', '좋아해'], ['나는', '사과를', '싫어해'], ['나는', '바나나를', '싫어해']] 2. Vectorize each words. '나는' = [0.1, 0.2, 0.9] '사과를' = [0.3, 0.5, 0.1] '바나나를' = [0.3, 0.5, 0.2]..

Machine Learning 2022.08.02

How to learning of DL

Loss function A gradient-based optimization strategy to train a model  f ( x ) " data-ke-type="html">HTML 삽입미리보기할 수 없는 소스 using some loss function   l ( f ( x i ) , y i ) where ( x i , y i ) " data-ke-type="html">HTML 삽입미리보기할 수 없는 소스 are some input-output pair.  It is used to help the model determine how "wrong" it i..

Deep Learning 2022.03.17
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nvidia-smi, yield from, d3js, batch size, docker-compose, axis, 3D Rotation Matrix, kafka, global variable, Filter, Sigmoid function, Regular Expression, selectall, Step Function, forward propagation, zeros, abstractmethod, textdistance, randn, classmethod,

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