chore(i18n,curriculum): update translations (#42969)

curriculum/challenges/portuguese/11-machine-learning-with-python/how-neural-networks-work/deep-learning-demystified.md

@@ -1,6 +1,6 @@
 ---
 id: 5e9a0e9ef99a403d019610cc
-title: Deep Learning Demystified
+title: Aprendizado profundo desmistificado
 challengeType: 11
 videoId: bejQ-W9BGJg
 dashedName: deep-learning-demystified
@@ -10,23 +10,23 @@ dashedName: deep-learning-demystified
 
 ## --text--
 
-How should you assign weights to input neurons before training your network for the first time?
+Como você deve atribuir pesos para inserir neurônios antes de treinar sua rede pela primeira vez?
 
 ## --answers--
 
-From smallest to largest.
+De menor para maior.
 
 ---
 
-Completely randomly.
+De modo completamente aleatório.
 
 ---
 
-Alphabetically.
+Alfabeticamente.
 
 ---
 
-None of the above.
+Nenhuma das anteriores.
 
 ## --video-solution--
 

curriculum/challenges/portuguese/11-machine-learning-with-python/how-neural-networks-work/how-convolutional-neural-networks-work.md

@@ -1,6 +1,6 @@
 ---
 id: 5e9a0e9ef99a403d019610cd
-title: How Convolutional Neural Networks work
+title: Como funcionam as Redes Neurais Convolucionais
 challengeType: 11
 videoId: Y5M7KH4A4n4
 dashedName: how-convolutional-neural-networks-work
@@ -10,19 +10,19 @@ dashedName: how-convolutional-neural-networks-work
 
 ## --text--
 
-When are Convolutional Neural Networks not useful?
+Quando as redes neurais convolucionais não são úteis?
 
 ## --answers--
 
-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.
+Se os dados não puderem parecer com uma imagem, ou se você puder reorganizar os elementos dos dados e ainda assim eles continuarem com a mesma utilidade.
 
 ---
 
-If your data is made up of different 2D or 3D images.
+Se seus dados forem compostos por diferentes imagens 2D ou 3D.
 
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-If your data is text or sound based.
+Se seus dados forem baseados em texto ou som.
 
 ## --video-solution--
 

curriculum/challenges/portuguese/11-machine-learning-with-python/how-neural-networks-work/how-deep-neural-networks-work.md

@@ -1,6 +1,6 @@
 ---
 id: 5e9a0e9ef99a403d019610ca
-title: How Deep Neural Networks Work
+title: Como as redes neurais profundas funcionam
 challengeType: 11
 videoId: zvalnHWGtx4
 dashedName: how-deep-neural-networks-work
@@ -10,19 +10,19 @@ dashedName: how-deep-neural-networks-work
 
 ## --text--
 
-Why is it better to calculate the gradient (slope) directly rather than numerically?
+Por que é melhor calcular o gradiente (curva) diretamente ao invés de numericamente?
 
 ## --answers--
 
-It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
+É computacionalmente caro voltar através de toda a rede neural e ajustar os pesos para cada camada da rede neural.
 
 ---
 
-It is more accurate.
+É mais preciso.
 
 ---
 
-There is no difference between the two methods.
+Não existe qualquer diferença entre os dois métodos.
 
 ## --video-solution--
 

curriculum/challenges/portuguese/11-machine-learning-with-python/how-neural-networks-work/recurrent-neural-networks-rnn-and-long-short-term-memory-lstm.md

@@ -1,6 +1,6 @@
 ---
 id: 5e9a0e9ef99a403d019610cb
-title: Recurrent Neural Networks RNN and Long Short Term Memory LSTM
+title: Redes neurais recorrentes RNN e a memória de curto e longo prazo LSTM
 challengeType: 11
 videoId: UVimlsy9eW0
 dashedName: recurrent-neural-networks-rnn-and-long-short-term-memory-lstm
@@ -10,19 +10,19 @@ dashedName: recurrent-neural-networks-rnn-and-long-short-term-memory-lstm
 
 ## --text--
 
-What are the main neural network components that make up a Long Short Term Memory network?
+Quais são os principais componentes de rede neural que compõem uma rede de memória de longo e curto prazo?
 
 ## --answers--
 
-New information and prediction.
+Novas informações e previsão.
 
 ---
 
-Prediction, collected possibilities, and selection.
+Previsão, possibilidades coletadas e seleção.
 
 ---
 
-Prediction, ignoring, forgetting, and selection.
+Previsão, capacidade de ignorar, capacidade de esquecer e seleção.
 
 ## --video-solution--