An annotated path to start with Machine Learning

“Do not worry about your difficulties in Mathematics. I can assure you mine are still greater.” (A. Einstein)   Machine Learning is becoming more and more widespread and, day after day, new computer scientists and engineers begin their long jump into this wonderful world. Unfortunately, the number of theories, algorithms, applications,…

ML Algorithms Addendum: Instance Based Learning

Contrary to the majority of machine learning algorithms, Instance-Based Learning is model-free, meaning that there are strong assumptions about the structure of regressors, classifiers or clustering functions. They are “simply” determined by the data, according to an affinity induced by a distance metric (the most common name for this approach…

ML Algorithms Addendum: Hebbian Learning

Hebbian Learning is one the most famous learning theories, proposed by the Canadian psychologist Donald Hebb in 1949, many years before his results were confirmed through neuroscientific experiments. Artificial Intelligence researchers immediately understood the importance of his theory when applied to artificial neural networks and, even if more efficient algorithms…

Hodgkin-Huxley spiking neuron model in Python

The Hodgkin-Huxley model (published on 1952 in The Journal of Physiology [1]) is the most famous spiking neuron model (also if there are simpler alternatives like the “Integrate-and-fire” model which performs quite well). It’s made up of a system of four ordinary differential equations that can be easily integrated using several…

Twitter Sentiment Analysis with Gensim Word2Vec and Keras Convolutional Networks

Fork Word2Vec (https://code.google.com/archive/p/word2vec/) offers a very interesting alternative to classical NLP based on term-frequency matrices. In particular, as each word is embedded into a high-dimensional vector, it’s possible to consider a sentence like a sequence of points that determine an implicit geometry. For this reason, the idea of considering 1D…

Keras-based Neural Artistic Style Transfer

Fork I’ve just moved my Keras-based Neural Artistic Style Transfer GIST to a dedicated repository: https://github.com/giuseppebonaccorso/Neural_Artistic_Style_Transfer. Please refer always to it because the GIST is not more maintained. See also: Neural artistic style transfer experiments with Keras – Giuseppe Bonaccorso Artistic style transfer using neural networks is a technique proposed by…

OpenAI-Gym Cartpole-v0 LSTM experiment with Keras (Theano)

OpenAI-Gym evaluation page: https://gym.openai.com/evaluations/eval_JxPKNwd1QjaofWkaE4aLfQ. Below there’s the whole Gist page containing the full Python code. It has been developed and tested with Theano/GPU support, but it can easily work with CPU-only support. Any comment or suggestion is welcome! View the code on Gist. See also: CIFAR-10 image classification with Keras ConvNet…