Category: Deep learning
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.
In this post we will return to the Pitchfork music data and use recurrent neural networks (a “deep learning” technique) to automatically generate band names.The DataFor this analysis, we will...continue reading.
Building a scaleable Deep Learning Serving Environment for Keras models using NVIDIA TensorRT Server and Google Cloud
In a recent project at STATWORX, my team and I developed a large scale deep learning application for image classification using Keras and Tensorflow. After developing the model, we needed...continue reading.
STATWORX welcomes you to our open workshop “Deep Learning in R and Keras” ! The workshop is designed for advanced R-users who are fluent in importing, processing and manipulating data....continue reading.
Last Christmas is one of the most popular Christmas tunes that were, are and will be out there. The song is written by the brilliant musician George Michael and was...continue reading.
Analyzing the relationship between the sample size and how it impacts on the accuracy in a classification modelcontinue reading.
Google AutoML Vision is a state-of-the-art cloud service from Google that is able to build deep learning models for image recognition completely fully automated and from scratch. In this post,...continue reading.
In unseren bisherigen Artikeln zu Data Science in Python haben wir uns mit der grundlegenden Syntax, Datenstrukturen, Arrays, der Datenvisualisierung und Manipulation/Selektion auseinander gesetzt. Was jetzt noch für den Einstieg...continue reading.
A guest post by @MaxMaPichler, MSc student in the Group for Theoretical Ecology / UR Artificial neural networks, especially deep neural networks and (deep) convolutions neural networks, have become increasingly popular...continue reading.
Well, what you hate is the way that math was taught to you. This post is a try to re-discover the beauty of learning math by finding a purpose, using...continue reading.
I have to admit my initial thoughts of deep learning were pessimistic and in order to not succumb to impostor syndrome, I put off learning any new techniques in the...continue reading.
The dropout approach developed by Hinton has been widely employed in deep learnings to prevent the deep neural network from overfitting, as shown in https://statcompute.wordpress.com/2017/01/02/dropout-regularization-in-deep-neural-networks. In the paper http://proceedings.mlr.press/v38/korlakaivinayak15.pdf, the...continue reading.