Lectures Video: Machine Learning for Physicists

Watch the videos on Apple iTunes or on the Lecture Videos Site of the University Erlangen-Nuremberg, or jump to the direct links below!

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Direct Links

Lecture 1: Introduction

Lecture 2: Training a Neural Network

Lecture 3: Training (Backpropagation Algorithm)

Lecture 4: Analyzing a network. Using the python framework “keras”

Lecture 5: Image classification

Lecture 6: Convolutional networks, Autoencoder

Lecture 7: Visualization of neuron activations (t-SNE method), Adaptive Gradient Descent Techniques

Lecture 8: Recurrent networks (LSTM)

Lecture 9: Word Vectors, Reinforcement Learning, REINFORCE (Policy Gradient)

Lecture 10: Policy Gradient (continued), Baseline, alphaGo, Q learning

Lecture 11: Q learning (finished), Restricted Boltzmann Machine

Lecture 12: Neural Network Applications in Science, Artificial Intelligence and Artificial Scientific Discovery

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