chore(i18n,curriculum): processed translations (#42868)
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id: 5e9a0e9ef99a403d019610cc
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title: Deep Learning Demystified
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title: 解密深度學習
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challengeType: 11
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videoId: bejQ-W9BGJg
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dashedName: deep-learning-demystified
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@ -10,23 +10,23 @@ dashedName: deep-learning-demystified
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## --text--
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How should you assign weights to input neurons before training your network for the first time?
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在你第一次訓練你的網絡之前,你應該如何給輸入層節點分配權重?
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## --answers--
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From smallest to largest.
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從小到大
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---
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Completely randomly.
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完全隨機的
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Alphabetically.
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按字母順序
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None of the above.
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以上都不對
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## --video-solution--
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---
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id: 5e9a0e9ef99a403d019610cd
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title: How Convolutional Neural Networks work
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title: 卷積神經網絡的工作原理
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challengeType: 11
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videoId: Y5M7KH4A4n4
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dashedName: how-convolutional-neural-networks-work
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@ -10,19 +10,19 @@ dashedName: how-convolutional-neural-networks-work
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## --text--
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When are Convolutional Neural Networks not useful?
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卷積神經網絡在什麼時候是沒有用的?
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## --answers--
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If your data can't be made to look like an image, or if you can rearrange elements of your data and it's still just as useful.
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當數據的組成形式不能像圖片存儲的數據格式一樣,或者說你的數據可以重新排列,它仍然可以被運用到卷積神經網絡中。
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---
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If your data is made up of different 2D or 3D images.
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如果你的數據是由 2D 或者 3D 圖片組成的。
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---
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If your data is text or sound based.
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如果你的數據是基於文本或者音頻的形式。
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## --video-solution--
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---
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id: 5e9a0e9ef99a403d019610ca
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title: How Deep Neural Networks Work
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title: 深度神經網絡的工作原理
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challengeType: 11
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videoId: zvalnHWGtx4
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dashedName: how-deep-neural-networks-work
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@ -10,19 +10,19 @@ dashedName: how-deep-neural-networks-work
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## --text--
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Why is it better to calculate the gradient (slope) directly rather than numerically?
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相比較數字的計算,爲什麼深度神經網絡可以更好地計算梯度(斜率)?
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## --answers--
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It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
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通過回溯整個神經網絡來更改每一層神經網絡的權重,在計算上來說是非常耗時的。
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It is more accurate.
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它更加準確。
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There is no difference between the two methods.
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這兩種方法之間沒有區別。
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## --video-solution--
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---
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id: 5e9a0e9ef99a403d019610cb
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title: Recurrent Neural Networks RNN and Long Short Term Memory LSTM
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title: 循環神經網絡 RNN 和長短期記憶 LSTM
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challengeType: 11
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videoId: UVimlsy9eW0
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dashedName: recurrent-neural-networks-rnn-and-long-short-term-memory-lstm
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@ -10,19 +10,19 @@ dashedName: recurrent-neural-networks-rnn-and-long-short-term-memory-lstm
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## --text--
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What are the main neural network components that make up a Long Short Term Memory network?
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構成長短期記憶網絡的主要神經網絡組件是什麼?
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## --answers--
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New information and prediction.
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新的信息和預測
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Prediction, collected possibilities, and selection.
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預測、收集的可能性和選擇
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Prediction, ignoring, forgetting, and selection.
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預測、忽視、遺忘和選擇
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## --video-solution--
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