In my GitHub repository (https://github.com/statcompute/MonotonicBinning), multiple R functions have been developed to implement the monotonic binning by using either iterative discretization or isotonic regression. With these functions, we can run...continue reading.
Normalizing flows are one of the lesser known, yet fascinating and successful architectures in unsupervised deep learning. In this post we provide a basic introduction to flows using tfprobability, an...continue reading.
I had cause a few years ago to read up quickly on AI. I don’t mean the same as people … Morecontinue reading.
Opening the black-box in complex models: SHAP values. What are they and how to draw conclusions from them? With R code example!continue reading.
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.
I’ve just updated The Popularity of Data Science Software to reflect my take on Gartner’s 2019 report, Magic Quadrant for Data Science and Machine Learning Platforms. To save you the...continue reading.
In past several weeks, I spent a tremendous amount of time on reading literature about automatic parameter tuning in the context of Machine Learning (ML), most of which can be...continue reading.
A call to all potential participants to the incoming BayesComp 2020 conference at the University of Florida in Gainesville, Florida, 7-10 January 2020, to submit proposals [to me] for contributed...continue 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.
Create a predictive model with the h2o package. H2o is a fantastic open source machine learning platform with many different algorithms. There is Graphical user interface, a Python interface and...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.
At the beginning of the new year I always want to clean up my photos on my phone. It just never happens. So now (like so many others I think)...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.
VAE is a generative model that leverages Neural Network as function approximator to model a continuous latent variable with intractable posterior distribution. If you are interested in the theory of...continue reading.
GIS / R / R News / Shiny / Visualization
Interactive visualization of geospatial data with R Shiny
April 17, 2021
