Learning of manifolds Also topological data analysis; other hip names to follow 2014-08-19 – 2020-06-23

Dimensionality reduction Wherein I teach myself, amongst other things, feature selection, how a sparse PCA works, and decide where to file multidimensional scaling 2015-03-22 – 2020-06-23

Probabilistic neural nets Machinelearnese for “Bayesian” 2017-01-11 – 2020-06-14

Tensorflow The framework to use for deep learning if you groupthink like Google 2016-07-11 – 2020-05-15

Convolutional neural networks 2017-11-10 – 2020-04-24

Learning summary statistics 2020-04-22

Learning Gamelan 2016-04-05 – 2020-04-06

Neural nets designing the fanciest usable differentiable loss surface 2016-10-14 – 2020-04-05

Deep learning as a dynamical system 2018-08-13 – 2020-04-02

Teaching computers to write music 2016-06-06 – 2020-03-25

Here’s how I would do art with machine learning if I had to 2016-06-06 – 2020-03-24

Learnable indexes and hashes 2018-01-12 – 2020-02-18

pytorch #torched 2018-05-04 – 2020-02-06

Recurrent neural networks 2016-06-16 – 2020-01-23

Why does deep learning work? despite the fact we are totally just making this shit up 2017-05-30 – 2019-10-09

Differentiable learning of automata 2016-10-14 – 2019-09-11

Compressing neural nets 2016-10-14 – 2019-05-27

Neural nets designing the fanciest usable differentiable loss surface 2016-10-14 – 2019-05-27

Overparameterization a.k.a. improper learning 2018-04-04 – 2018-12-11

Compressing artificial neural networks 2016-10-12 – 2018-10-23

Generalisation in neural networks Generalisation for street fighters 2017-02-12 – 2017-06-20

Entity embeddings 2017-04-01

Random neural networks 2017-02-17 – 2017-02-19

Garbled highlights from NIPS 2016 2016-12-05 – 2017-02-03

Neural network activation functions 2017-01-12

Pattern machine 2011-06-27 – 2015-11-24