From Exploration to Production — Bridging the Deployment Gap for Deep Learning
Tag: Data Science
Time Series Forecasting with Machine Learning Models
Multiplicative LSTM for sequence-based Recommenders
Managing isolated Environments with PySpark
Data Science in Production: Packaging, Versioning and Continuous Integration
Efficient UD(A)Fs with PySpark
A hybrid supervised/unsupervised approach to network anomaly detection
Declarative Thinking and Programming
Anomaly Detection: (Dis-)advantages of k-means clustering