chore(i18n,learn): processed translations (#45432)

curriculum/challenges/espanol/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-evaluating-the-model.md

@@ -1,8 +1,12 @@
 ---
 id: 5e8f2f13c4cdbe86b5c72d99
-title: 'Convolutional Neural Networks: Evaluating the Model'
+title: 'Redes Neurales Convolucionales: Evaluando el Modelo'
 challengeType: 11
 videoId: eCATNvwraXg
+bilibiliIds:
+  aid: 933030136
+  bvid: BV1hM4y1g7Bx
+  cid: 409132265
 dashedName: convolutional-neural-networks-evaluating-the-model
 ---
 
@@ -10,19 +14,19 @@ dashedName: convolutional-neural-networks-evaluating-the-model
 
 ## --text--
 
-What is **not** a good way to increase the accuracy of a convolutional neural network?
+¿Qué **no** es una buena manera de incrementar la precisión de una red neuronal convolucional?
 
 ## --answers--
 
-Augmenting the data you already have.
+Aumentando los datos que ya tiene.
 
 ---
 
-Using a pre-trained model.
+Usando un model pre-entrenado.
 
 ---
 
-Using your test data to retrain the model.
+Usando tus datos de prueba para re entrenar el modelo.
 
 ## --video-solution--
 

curriculum/challenges/espanol/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-picking-a-pretrained-model.md

@@ -1,8 +1,12 @@
 ---
 id: 5e8f2f13c4cdbe86b5c72d9a
-title: 'Convolutional Neural Networks: Picking a Pretrained Model'
+title: 'Redes Neuronales Convolucionales: Eligiendo un Modelo Pre-entrenado'
 challengeType: 11
 videoId: h1XUt1AgIOI
+bilibiliIds:
+  aid: 463063633
+  bvid: BV1qL411x73q
+  cid: 409132626
 dashedName: convolutional-neural-networks-picking-a-pretrained-model
 ---
 
@@ -10,7 +14,7 @@ dashedName: convolutional-neural-networks-picking-a-pretrained-model
 
 ## --text--
 
-Fill in the blanks below to use Google's pre-trained MobileNet V2 model as a base for a convolutional neural network:
+Completa los siguientes espacios en blanco para utilizar el modelo pre-entrenado MobileNet V2 de Google como base para una red neuronal convolucional:
 
 ```py
 base_model = tf.__A__.applications.__B__(input_shape=(160, 160, 3),

curriculum/challenges/espanol/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning.md

@@ -1,8 +1,12 @@
 ---
 id: 5e8f2f13c4cdbe86b5c72da3
-title: Reinforcement Learning With Q-Learning
+title: Aprendizaje Reforzado con Q-Learning
 challengeType: 11
 videoId: Cf7DSU0gVb4
+bilibiliIds:
+  aid: 463025802
+  bvid: BV1iL411x7L6
+  cid: 409138811
 dashedName: reinforcement-learning-with-q-learning
 ---
 
@@ -10,19 +14,19 @@ dashedName: reinforcement-learning-with-q-learning
 
 ## --text--
 
-The key components of reinforcement learning are...
+Los componente clave del Aprendizaje Reforzado son...
 
 ## --answers--
 
-environment, representative, state, reaction, and reward.
+entorno, representatividad, estado, reacción, y recompensa.
 
 ---
 
-environment, agent, state, action, and reward.
+entorno, agente, estado, acción, y recompensa.
 
 ---
 
-habitat, agent, state, action, and punishment.
+habitat, agente, estado, acción, y castigo.
 
 ## --video-solution--