Oxford

Lecture 10 Convolutional Neural Networks (Oxford)

Lecture 11 Max-margin learning, transfer and memory networks (Oxford)

Lecture 12 Recurrent Neural Nets and LSTMs (Oxford)

Lecture 13 Alex Graves on Hallucination with RNNs (Oxford)

Lecture 14 Karol Gregor on Variational Autoencoders and Image Generation (Oxford)

Lecture 15 Deep Reinforcement Learning – Policy search (Oxford)

Lecture 16 Reinforcement learning and neuro-dynamic programming (Oxford)

Lecture 2 Linear models (Oxford)

Lecture 3 Maximum likelihood and information (Oxford)

Lecture 4 Regularization, model complexity and data complexity (part 1) (Oxford)

Lecture 5 Regularization, model complexity and data complexity (part 2) (Oxford)

Lecture 6 Optimization (Oxford)

Lecture 7 Logistic regression, a Torch approach (Oxford)

Lecture 8 Modular back-propagation, logistic regression and Torch (Oxford)

Lecture 9 Neural networks and modular design in Torch (Oxford)

001 Introduction to Quantum Mechanics, Probability Amplitudes and Quantum States (Oxford)

002 Dirac Notation and the Energy Representation (Oxford)

003 Operators and Measurement (Oxford)

026 Hydrogen part 2 Emission Spectra (Oxford)

027 Hydrogen part 3 Eigenfunctions (Oxford)

004 Commutators and Time Evolution (Oxford)

005 Further TDSE and the Position Representation (Oxford)

006 Wavefunctions for Well Defined Momentum (Oxford)

007 Back to Two-Slit Interference, Generalization to Three Dimensions and the Virial Theorem (Oxford)

008 The Harmonic Oscillator and the Wavefunctions of its Stationary States (Oxford)