Unsupervised machine learning looks for hidden structure in “unlabeled” data, i.e. a classification or categorisation that is not included in the observations. Hierarchical clustering will reveal a “cluster of six” Labour MPs as...continue reading.
The aim of this post is to illustrate how deep learning is being applied in cancer immunotherapy (Immuno-oncology or Immunooncology) – a cancer treatment strategy, where the aim is to...continue reading.
The aim of this post is to illustrate how deep learning is being applied in cancer immunotherapy (Immuno-oncology or Immunooncology) – a cancer treatment strategy, where the aim is to...continue reading.
I just uploaded my slides on probabilistic Topic Modeling with LDA that give an overview of the theory, the basic … Read More →continue reading.
In this post we will train an autoencoder to detect credit card fraud. We will also demonstrate how to train Keras models in the cloud using CloudML. The basis of...continue reading.
In this post we will train an autoencoder to detect credit card fraud. We will also demonstrate how to train Keras models in the cloud using CloudML. The basis of...continue reading.
The kerasformula package offers a high-level interface for the R interface to Keras. It’s main interface is the kms function, a regression-style interface to keras_model_sequential that uses formulas and sparse...continue reading.
The kerasformula package offers a high-level interface for the R interface to Keras. It’s main interface is the kms function, a regression-style interface to keras_model_sequential that uses formulas and sparse...continue reading.
$tf.cond$ is used to define if-statement in tensorflow operation graph. It has the following signature: cond( pred, true\_fn=None, false\_fn=None)An important point that needs to be noted is that $tf.cond$ evaluates...continue reading.
Using Keras to predict customer churn based on the IBM Watson Telco Customer Churn dataset. We also demonstrate using the lime package to help explain which features drive individual model...continue reading.
Using Keras to predict customer churn based on the IBM Watson Telco Customer Churn dataset. We also demonstrate using the lime package to help explain which features drive individual model...continue reading.
We are excited to announce the availability of the cloudml package, which provides an R interface to Google Cloud Machine Learning Engine. CloudML provides a number of services including on-demand...continue reading.
We are excited to announce the availability of the cloudml package, which provides an R interface to Google Cloud Machine Learning Engine. CloudML provides a number of services including on-demand...continue reading.
In this post we will use Keras to classify duplicated questions from Quora. Our implementation is inspired by the Siamese Recurrent Architecture, with modifications to the similarity measure and the...continue reading.
In this post we will use Keras to classify duplicated questions from Quora. Our implementation is inspired by the Siamese Recurrent Architecture, with modifications to the similarity measure and the...continue reading.
Word embedding is a method used to map words of a vocabulary to dense vectors of real numbers where semantically similar words are mapped to nearby points. In this example...continue reading.
Word embedding is a method used to map words of a vocabulary to dense vectors of real numbers where semantically similar words are mapped to nearby points. In this example...continue reading.
A try to automatize the data preparation discretization stage. Converting numerical variables into categorical to be used in real scenarios.continue reading.
In this post, we’ll review three advanced techniques for improving the performance and generalization power of recurrent neural networks. We’ll demonstrate all three concepts on a temperature-forecasting problem, where you...continue reading.
In this post, we’ll review three advanced techniques for improving the performance and generalization power of recurrent neural networks. We’ll demonstrate all three concepts on a temperature-forecasting problem, where you...continue reading.
GIS / R / R News / Shiny / Visualization
Interactive visualization of geospatial data with R Shiny
April 17, 2021
