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curriculum/challenges/chinese/11-machine-learning-with-python/machine-learning-with-python-projects/book-recommendation-engine-using-knn.md
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id: 5e46f8e3ac417301a38fb92f
title: Book Recommendation Engine using KNN
challengeType: 10
dashedName: book-recommendation-engine-using-knn
---

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curriculum/challenges/chinese/11-machine-learning-with-python/machine-learning-with-python-projects/cat-and-dog-image-classifier.md
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id: 5e46f8dcac417301a38fb92e
title: Cat and Dog Image Classifier
challengeType: 10
dashedName: cat-and-dog-image-classifier
---

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curriculum/challenges/chinese/11-machine-learning-with-python/machine-learning-with-python-projects/linear-regression-health-costs-calculator.md
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id: 5e46f8edac417301a38fb930
title: Linear Regression Health Costs Calculator
challengeType: 10
dashedName: linear-regression-health-costs-calculator
---

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curriculum/challenges/chinese/11-machine-learning-with-python/machine-learning-with-python-projects/neural-network-sms-text-classifier.md
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id: 5e46f8edac417301a38fb931
title: Neural Network SMS Text Classifier
challengeType: 10
dashedName: neural-network-sms-text-classifier
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curriculum/challenges/chinese/11-machine-learning-with-python/machine-learning-with-python-projects/rock-paper-scissors.md
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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.