chore(i8n,learn): processed translations

This commit is contained in:
Crowdin Bot
2021-02-06 04:42:36 +00:00
committed by Mrugesh Mohapatra
parent 15047f2d90
commit e5c44a3ae5
3274 changed files with 172122 additions and 14164 deletions

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---
id: 5e9a0e9ef99a403d019610cc
title: Deep Learning Demystified
challengeType: 11
videoId: bejQ-W9BGJg
dashedName: deep-learning-demystified

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---
id: 5e9a0e9ef99a403d019610cd
title: How Convolutional Neural Networks work
challengeType: 11
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dashedName: how-convolutional-neural-networks-work

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---
id: 5e9a0e9ef99a403d019610ca
title: How Deep Neural Networks Work
challengeType: 11
videoId: zvalnHWGtx4
dashedName: how-deep-neural-networks-work

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---
id: 5e9a0e9ef99a403d019610cb
title: Recurrent Neural Networks RNN and Long Short Term Memory LSTM
challengeType: 11
videoId: UVimlsy9eW0
dashedName: recurrent-neural-networks-rnn-and-long-short-term-memory-lstm

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---
id: 5e46f8e3ac417301a38fb92f
title: Book Recommendation Engine using KNN
challengeType: 10
dashedName: book-recommendation-engine-using-knn
---

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---
id: 5e46f8dcac417301a38fb92e
title: Cat and Dog Image Classifier
challengeType: 10
dashedName: cat-and-dog-image-classifier
---

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---
id: 5e46f8edac417301a38fb930
title: Linear Regression Health Costs Calculator
challengeType: 10
dashedName: linear-regression-health-costs-calculator
---

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---
id: 5e46f8edac417301a38fb931
title: Neural Network SMS Text Classifier
challengeType: 10
dashedName: neural-network-sms-text-classifier
---

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---
id: 5e46f8d6ac417301a38fb92d
title: Rock Paper Scissors
challengeType: 10
dashedName: rock-paper-scissors
---
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For this challenge, you will create a program to play Rock, Paper, Scissors. A program that picks at random will usually win 50% of the time. To pass this challenge your program must play matches against four different bots, winning at least 60% of the games in each match.
You can access [the full project description and starter code on repl.it](https://repl.it/@freeCodeCamp/fcc-rock-paper-scissors).
You can access [the full project description and starter code on repl.it](https://repl.it/github/freeCodeCamp/boilerplate-rock-paper-scissors).
After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.

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id: 5e8f2f13c4cdbe86b5c72da6
title: Conclusion
challengeType: 11
videoId: LMNub5frQi4
dashedName: conclusion

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id: 5e8f2f13c4cdbe86b5c72d99
title: 'Convolutional Neural Networks: Evaluating the Model'
challengeType: 11
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dashedName: convolutional-neural-networks-evaluating-the-model

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id: 5e8f2f13c4cdbe86b5c72d9a
title: 'Convolutional Neural Networks: Picking a Pretrained Model'
challengeType: 11
videoId: h1XUt1AgIOI
dashedName: convolutional-neural-networks-picking-a-pretrained-model

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id: 5e8f2f13c4cdbe86b5c72d97
title: 'Convolutional Neural Networks: The Convolutional Layer'
challengeType: 11
videoId: LrdmcQpTyLw
dashedName: convolutional-neural-networks-the-convolutional-layer

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---
id: 5e8f2f13c4cdbe86b5c72d96
title: Convolutional Neural Networks
challengeType: 11
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dashedName: convolutional-neural-networks

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---
id: 5e8f2f13c4cdbe86b5c72d8e
title: 'Core Learning Algorithms: Building the Model'
challengeType: 11
videoId: 5wHw8BTd2ZQ
dashedName: core-learning-algorithms-building-the-model

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---
id: 5e8f2f13c4cdbe86b5c72d8d
title: 'Core Learning Algorithms: Classification'
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dashedName: core-learning-algorithms-classification

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---
id: 5e8f2f13c4cdbe86b5c72d8f
title: 'Core Learning Algorithms: Clustering'
challengeType: 11
videoId: 8sqIaHc9Cz4
dashedName: core-learning-algorithms-clustering

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---
id: 5e8f2f13c4cdbe86b5c72d90
title: 'Core Learning Algorithms: Hidden Markov Models'
challengeType: 11
videoId: IZg24y4wEPY
dashedName: core-learning-algorithms-hidden-markov-models

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---
id: 5e8f2f13c4cdbe86b5c72d8c
title: 'Core Learning Algorithms: The Training Process'
challengeType: 11
videoId: _cEwvqVoBhI
dashedName: core-learning-algorithms-the-training-process

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---
id: 5e8f2f13c4cdbe86b5c72d8b
title: 'Core Learning Algorithms: Training and Testing Data'
challengeType: 11
videoId: wz9J1slsi7I
dashedName: core-learning-algorithms-training-and-testing-data

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---
id: 5e8f2f13c4cdbe86b5c72d91
title: 'Core Learning Algorithms: Using Probabilities to make Predictions'
challengeType: 11
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dashedName: core-learning-algorithms-using-probabilities-to-make-predictions

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---
id: 5e8f2f13c4cdbe86b5c72d8a
title: 'Core Learning Algorithms: Working with Data'
challengeType: 11
videoId: u85IOSsJsPI
dashedName: core-learning-algorithms-working-with-data

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---
id: 5e8f2f13c4cdbe86b5c72d89
title: Core Learning Algorithms
challengeType: 11
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dashedName: core-learning-algorithms

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---
id: 5e8f2f13c4cdbe86b5c72d98
title: Creating a Convolutional Neural Network
challengeType: 11
videoId: kfv0K8MtkIc
dashedName: creating-a-convolutional-neural-network

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---
id: 5e8f2f13c4cdbe86b5c72d87
title: 'Introduction: Machine Learning Fundamentals'
challengeType: 11
videoId: KwL1qTR5MT8
dashedName: introduction-machine-learning-fundamentals

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---
id: 5e8f2f13c4cdbe86b5c72d88
title: Introduction to TensorFlow
challengeType: 11
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dashedName: introduction-to-tensorflow

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---
id: 5e8f2f13c4cdbe86b5c72da1
title: 'Natural Language Processing With RNNs: Building the Model'
challengeType: 11
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dashedName: natural-language-processing-with-rnns-building-the-model

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---
id: 5e8f2f13c4cdbe86b5c72da0
title: 'Natural Language Processing With RNNs: Create a Play Generator'
challengeType: 11
videoId: j5xsxjq_Xk8
dashedName: natural-language-processing-with-rnns-create-a-play-generator

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---
id: 5e8f2f13c4cdbe86b5c72d9f
title: 'Natural Language Processing With RNNs: Making Predictions'
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---
id: 5e8f2f13c4cdbe86b5c72d9c
title: 'Natural Language Processing With RNNs: Part 2'
challengeType: 11
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dashedName: natural-language-processing-with-rnns-part-2

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---
id: 5e8f2f13c4cdbe86b5c72d9d
title: 'Natural Language Processing With RNNs: Recurring Neural Networks'
challengeType: 11
videoId: bX5681NPOcA
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---
id: 5e8f2f13c4cdbe86b5c72d9e
title: 'Natural Language Processing With RNNs: Sentiment Analysis'
challengeType: 11
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dashedName: natural-language-processing-with-rnns-sentiment-analysis

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---
id: 5e8f2f13c4cdbe86b5c72da2
title: 'Natural Language Processing With RNNs: Training the Model'
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dashedName: natural-language-processing-with-rnns-training-the-model

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---
id: 5e8f2f13c4cdbe86b5c72d9b
title: Natural Language Processing With RNNs
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dashedName: natural-language-processing-with-rnns

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---
id: 5e8f2f13c4cdbe86b5c72d93
title: 'Neural Networks: Activation Functions'
challengeType: 11
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dashedName: neural-networks-activation-functions

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---
id: 5e8f2f13c4cdbe86b5c72d95
title: 'Neural Networks: Creating a Model'
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dashedName: neural-networks-creating-a-model

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---
id: 5e8f2f13c4cdbe86b5c72d94
title: 'Neural Networks: Optimizers'
challengeType: 11
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dashedName: neural-networks-optimizers

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---
id: 5e8f2f13c4cdbe86b5c72d92
title: Neural Networks with TensorFlow
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dashedName: neural-networks-with-tensorflow

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---
id: 5e8f2f13c4cdbe86b5c72da5
title: 'Reinforcement Learning With Q-Learning: Example'
challengeType: 11
videoId: RBBSNta234s
dashedName: reinforcement-learning-with-q-learning-example

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---
id: 5e8f2f13c4cdbe86b5c72da4
title: 'Reinforcement Learning With Q-Learning: Part 2'
challengeType: 11
videoId: DX7hJuaUZ7o
dashedName: reinforcement-learning-with-q-learning-part-2

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---
id: 5e8f2f13c4cdbe86b5c72da3
title: Reinforcement Learning With Q-Learning
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