Category: Machine learning
Not everybody who wants to get into deep learning has a strong background in math or programming. This post elaborates on a concepts-driven, abstraction-based way to learn what it’s all...continue reading.
I am a co-organiser of the International Workshop on Computational Economics and Econometrics, taking place this year on 3-5 July … Morecontinue reading.
This method can discretize a variable taking into consideration the target variable, similar to what decision tree do but with gain ratio.continue reading.
In the previous post (https://statcompute.wordpress.com/2019/02/03/sobol-sequence-vs-uniform-random-in-hyper-parameter-optimization), it is shown how to identify the optimal hyper-parameter in a General Regression Neural Network by using the Sobol sequence and the uniform random generator...continue reading.
Hello again! Typically I would start by describing a complicated problem that can be solved using machine or deep learning methods, but today I want to do something different, I...continue reading.
Sometimes, deep learning is seen – and welcomed – as a way to avoid laborious preprocessing of data. However, there are cases where preprocessing of sorts does not only help...continue reading.
Tuning hyper-parameters might be the most tedious yet crucial in various machine learning algorithms, such as neural networks, svm, or boosting. The configuration of hyper-parameters not only impacts the computational...continue reading.
Mostly when thinking of Variational Autoencoders (VAEs), we picture the prior as an isotropic Gaussian. But this is by no means a necessity. The Vector Quantised Variational Autoencoder (VQ-VAE) described...continue reading.
What are GANs? Some time ago, I showed you how to create a simple Convolutional Neural Network (ConvNet) for satellite imagery classification using Keras. ConvNets are not the only cool...continue reading.
TensorFlow Probability offers a vast range of functionality ranging from distributions over probabilistic network layers to probabilistic inference. It works seamlessly with core TensorFlow and (TensorFlow) Keras. In this post,...continue reading.