Packages by Giancarlo Vercellino

audrex — 2.0.1

Automatic Dynamic Regression using Extreme Gradient Boosting

codez — 1.0.0

Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on Tensorflow

dymo — 1.1.0

Dynamic Mode Decomposition for Multivariate Time Feature Prediction

hmix — 1.0.2

Hidden Markov Model for Predicting Time Sequences with Mixture Sampling

janus — 1.0.0

Optimized Recommending System Based on 'tensorflow'

jenga — 1.3.0

Fast Extrapolation of Time Features using K-Nearest Neighbors

lambdaTS — 1.1

Variational Seq2Seq Model with Lambda Transformer for Time Series Analysis

naive — 1.2.3

Empirical Extrapolation of Time Feature Patterns

proteus — 1.1.4

Multiform Seq2Seq Model for Time-Feature Analysis

segen — 1.1.0

Sequence Generalization Through Similarity Network

sense — 1.1.0

Automatic Stacked Ensemble for Regression Tasks

snap — 1.1.0

Simple Neural Application

spinner — 1.1.0

An Implementation of Graph Net Architecture Based on 'torch'

spooky — 1.4.0

Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling

tetragon — 1.3.0

Automatic Sequence Prediction by Expansion of the Distance Matrix