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 notebookand 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 -
Navigate to the directory
cd Machine-Learning-Applications -
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