robinvanschaik

RWKV-LM

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

tsfresh

Automatic extraction of relevant features from time series:

examples

TensorFlow examples

metaseq

Repo for external large-scale work

awesome-reMarkable

A curated list of projects related to the reMarkable tablet

Kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

Merlion

Merlion: A Machine Learning Framework for Time Series Intelligence

neuralforecast

Scalable and user friendly neural :brain: forecasting algorithms.

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

uda

Unsupervised Data Augmentation (UDA)

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

transformer-deploy

Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀

vertex-ai-samples

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

python-holidays

Generate and work with holidays in Python

pytorch-ts

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

tsfel

An intuitive library to extract features from time series.

n-beats

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

lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

DeepLearningForTimeSeriesForecasting

A tutorial demonstrating how to implement deep learning models for time series forecasting

M5-methods

Data, Benchmarks, and methods submitted to the M5 forecasting competition

Sklearn-genetic-opt

ML hyperparameters tuning and features selection, using evolutionary algorithms.

cond_rnn

Conditional RNNs for Tensorflow / Keras.

nbeatsx

pgbm

Probabilistic Gradient Boosting Machines

remarkable-gtd-templates

Remarkable Gettings Things Done Templates

PlannerPDF

Generate a PDF Planner for the Remarkable Platform

remarkable-bujo

Bullet Journal templates for the reMarkable (2) paper tablet

gluonts-hierarchical-ICML-2021

sire

📈 SiRE (Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data), accepted by CIKM'2022 🗽

landscape-pdf

Utility to convert a pdf for viewing in landscape mode