Bidirectional Encoder Representations from Transformers (BERT)
Comparing Bidirectional Encoder Representations from Transformers (BERT) with DistilBERT and Bidirectional Gated Recurrent Unit (BGRU) for anti-social online behavior detection
Comparing Bidirectional Encoder Representations from Transformers (BERT) with DistilBERT and Bidirectional Gated Recurrent Unit (BGRU) for anti-social online behavior detection
Estimating shopper preferences and price elasticities in a retail grocery setting.
Application of state-of-the-art text classification techniques ELMo and ULMFiT to A Dataset of Peer Reviews (PeerRead)
Credit risk analytics using deep learning survival analysis
Developing a Sequence-to-Sequence model to generate news headlines – trained on real-world articles from US news publications – and building a text classifier utilising these headlines.
Individual Treatment Effect Estimation using a Residual Neural Network Architecture
This blog post deals with convolutional neural networks applied to a structured dataset with the aim to forecast sales.
This blog post deals with generative models applied to an imbalanced dataset of credit ratings.
Hierarchical Attention Networks - An Introduction
Introducing Recurrent Neural Networks with Long-Short-Term Memory and Gated Recurrent Unit to predict reported Crime Incident
Application of state-of-the-art text analysis technique ULMFiT to a Twitter Dataset
A simple introduction to convolutional neural networks
Prediction of financial time series using LSTM networks
In this blog, we present the practical use of deep learning in computer vision.
Candidate2vec - a deep dive into word embeddings
Sentiment Analysis for IMDB Movie Reviews
Exploring and applying current trends in machine learning to a large scale product recommendation based on implicit feedback.
The goal of this blog is an introduction to image captioning, an explanation of a comprehensible model structure and an implementation of that model.
This blog post is a guide to help readers build a neural network from the very basics.
An introduction to deploy the deep learning model
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