Analysis of social media behavior of the 2020 presidential election candidates
This blog post analyzes the tweets of the 2020 presidential candidates using Fasttext and CNN
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
Economic Uncertainty Identification
Identification of Economic Uncertainty from Newspaper Articles Using State of the Art Models.
Generating Synthetic Comments to Balance Data for Text Classification
Generating toxic comment text using GPT-2 to improve classification when data for one class is sparse
SHOPPER: A Probabalistic Consumer Choice Model
Estimating shopper preferences and price elasticities in a retail grocery setting.
Big Peer Review Challenge
Application of state-of-the-art text classification techniques ELMo and ULMFiT to A Dataset of Peer Reviews (PeerRead)
Deep Learning for Survival Analysis
Credit risk analytics using deep learning survival analysis
State Of The Art Text Summarisation Techniques
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.
Causal Neural Networks
Individual Treatment Effect Estimation using a Residual Neural Network Architecture
Uncertainty in Profit Scoring (Bayesian Deep Learning)
Application of Bayesian Deep Learning to Profit Scoring
Building a LDA-based Book Recommender System
A Book Recommender System
Convolutional Neural Networks - sales forecast
This blog post deals with convolutional neural networks applied to a structured dataset with the aim to forecast sales.
Generative Models
This blog post deals with generative models applied to an imbalanced dataset of credit ratings.
Opening the black box of machine learning
Opening the black-box: state-of-the-art in explaining opaque ML/DL models
Text Classification with Hierarchical Attention Network
Hierarchical Attention Networks - An Introduction
Crime and Neural Nets
Introducing Recurrent Neural Networks with Long-Short-Term Memory and Gated Recurrent Unit to predict reported Crime Incident
ULMFiT: State-of-the-Art in Text Analysis
Application of state-of-the-art text analysis technique ULMFiT to a Twitter Dataset
Convolutional Neural Networks (CNN)
A simple introduction to convolutional neural networks
Financial Time Series Predicting with Long Short-Term Memory
Prediction of financial time series using LSTM networks
Image Analysis: Introduction to deep learning for computer vision
In this blog, we present the practical use of deep learning in computer vision.
Numeric representation of text documents: doc2vec how it works and how you implement it
Candidate2vec - a deep dive into word embeddings
Text Mining - Sentiment Analysis
Sentiment Analysis for IMDB Movie Reviews
Wide and Deep Learning Model for Grocery Product Recommendations
Exploring and applying current trends in machine learning to a large scale product recommendation based on implicit feedback.
Image Captioning
The goal of this blog is an introduction to image captioning, an explanation of a comprehensible model structure and an implementation of that model.
Neural Network Fundamentals
This blog post is a guide to help readers build a neural network from the very basics.
Neural Networks into Production
An introduction to deploy the deep learning model