tutorials

How to run the notebook on Ubuntu 20.04

Checkout and build DiffKt.
Install Anaconda.
Create an Anaconda enviroment with the following command conda env create -f /diffkt/tutorials/enviroment.yml
You now have a conda enviroment call diffkt, activate it conda activate diffkt
Start Jupyter notebook server jupyter notebook
A webpage will show up in your browser, select the notebook you want to run.

Name		Name	Last commit message	Last commit date
parent directory ..
resources		resources
3d_nonlinear_regression.ipynb		3d_nonlinear_regression.ipynb
README.md		README.md
broadcasting.ipynb		broadcasting.ipynb
environment.yml		environment.yml
exponential_distribution_mle_gradient_descent.ipynb		exponential_distribution_mle_gradient_descent.ipynb
indexing.ipynb		indexing.ipynb
intro_to_differentiable_programming.ipynb		intro_to_differentiable_programming.ipynb
linear_regression_gradient_descent.ipynb		linear_regression_gradient_descent.ipynb
linear_regression_user_defined_types.ipynb		linear_regression_user_defined_types.ipynb
logistic_regression_gradient_descent.ipynb		logistic_regression_gradient_descent.ipynb
mass_spring.ipynb		mass_spring.ipynb
mass_spring_jit.ipynb		mass_spring_jit.ipynb
model.ipynb		model.ipynb
multivariable_linear_regression_gradient_descent.ipynb		multivariable_linear_regression_gradient_descent.ipynb
neural_network_sgd.ipynb		neural_network_sgd.ipynb
neural_network_user_defined_types.ipynb		neural_network_user_defined_types.ipynb
normal_mle_gradient_descent.ipynb		normal_mle_gradient_descent.ipynb
simple_parabola_gradient_descent.ipynb		simple_parabola_gradient_descent.ipynb
user_defined_types.ipynb		user_defined_types.ipynb

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