Deep-Learning-with-Jax

day_01_exercise_intro

Exercise on an introduction to the python development framework.

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day_02_exercise_optimization

Exercise on gradient descent by hand and via autograd in Jax.

day_03_exercise_algebra

Exercise on basics of algebra, curve fitting and singular value decomposition.

day_04_exercise_statistics

Exercise on statistics and distributions: mean and variance, correlation, gaussians.

day_05_exercise_neural_networks

Exercise on the MNIST-data set, artificial neurons, forward and backward pass.

day_06_exercise_cnn

Exercise on the convolution operation and convolutional neural networks.

day_07_exercise_brain_decode

Exercise on convolutional neural networks about how use them to decode brain waves.

day_08_exercise_interpretability

Exercise on interpretability with integrated gradients.

day_09_exercise_sequence_processing

Exercise on generative language modelling in Jax.