Machine-Learning-Applications
An overview of various projects involving real life applications of Machine Learning!
View this repository in VS Code by clicking here
To Launch all Python Notebook files (.ipynb):
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Click here
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Choose a project and open a file
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You can now look through the code!
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To interact with and run the code, click on the 'Execute on Binder' button on the top right of the screen. (This will take a considerable amount of time to load)
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Once loaded, you can download the file to save your changes
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You can also download the .ipynb files in this repository and upload them in Google Colab here
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Alternatively, if you want to run .ipynb files on your local machine, you can download jupyter notebook by running
pip install notebook
and then runningjupyter notebook
. Read more here
To Run the Python files (.py):
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Download the code
git clone https://github.com/SJUSATA/Machine-Learning-Applications.git
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Navigate to the directory
cd Machine-Learning-Applications
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Follow the instructions in your specific project's folder
Additional Resources
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Ted Talk: The Wonderful and Terrifying Implications of Computers that Can Learn
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Ted Talk: The Jobs We'll Lose to Machines -- and the Ones We Won't
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DeepMind:
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OpenAI:
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Datasets for ML Applications can be found on Kaggle and Google Dataset Search