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6289nlp_proj

autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

cnn_limit_order_book

modeling limit order book data with the CNN model

databook_python

IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz

deeptime

Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

dl_notebook

An array of short notebooks demonstrating ideas

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

etsformer

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

etsformer-pytorch

Implementation of ETSformer, state of the art time-series Transformer, in Pytorch

ift6135_programming

memory-transformer-xl

A variant of Transformer-XL where the memory is updated not with a queue, but with attention

mogrifier

Usable implementation of Mogrifier, a circuit for enhancing LSTMs and potentially other networks, from Deepmind

n-beats

Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

n-hits

nlp-with-transformers

Jupyter notebooks for the Natural Language Processing with Transformers book

pandas-in-action

Complete source code (datasets and Jupyter Notebooks) for Pandas In Action

statswithjuliabook

timeseries_limit_order_book

A set of transformer and CNN models that make predictions based on limit order book

tiny_python_projects

Learning Python through test-driven development of games and puzzles

transformer-xl

uvadlc_notebooks

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch