Reverse Dependencies of sktime

The following projects have a declared dependency on sktime:

• atom-ml — A Python package for fast exploration of machine learning pipelines
• AugmentTS — Time Series Forecasting and Data Augmentation using Deep Generative Models
• autoPyTorch — Auto-PyTorch searches neural architectures using smac
• batch-prediction-pipeline — no summary
• batch-prediction-pipeline-self — no summary
• bciavm — bciAVM is a machine learning pipeline used to predict property prices.
• cat-spend-training-pipeline — no summary
• climaticai — climaticai is a library that builds, optimizes, and evaluates machine learning pipelines
• deepof — no summary
• demand-pred-model — An ML model to predict demand in E-commerce
• eeg-emotion-recognition — no summary
• energy-consumption-forecasting — A Machine Learning project on Denmark's Energy Consumption.
• evalml — an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions
• fedot — Automated machine learning framework for composite pipelines
• fedot-ind — Time series analysis framework
• forecast-ar — Automation of forecast models testing, combining and predicting
• forecast-combine — Automation of forecast models testing, combining and predicting
• g-batch-prediction-pipeline — no summary
• g-training-pipeline — no summary
• gpforecaster — Hierarchical time series forecasting model using Gaussian Processes
• hierarchical-prophet — no summary
• lightwood — Lightwood is Legos for Machine Learning.
• loadmydata — Collections of utility functions to download open-source data sets.
• lp-Aicloud — this a aicloud
• lsts — A lightweight, fast, advanced deep learning time series package for long and short-term forecast and missing value imputation of land surface variables.
• mdata — no summary
• metats — Meta-Learning for Time Series Forecasting
• mip-training-pipeline — no summary
• mlflavors — MLflavors: A collection of custom MLflow flavors.
• mlops_batch_prediction_pipeline — no summary
• mlops_training_pipeline — no summary
• mngs — For lazy python users (monogusa people in Japanse), especially in ML/DSP fields
• oracle-automlx — Automated Machine Learning with Explainability
• prophet-numpyro — no summary
• prophetverse — no summary
• pycaret — PyCaret - An open source, low-code machine learning library in Python.
• pycaret-ts-alpha — PyCaret - An open source, low-code machine learning library in Python.
• pyspi — Library for pairwise analysis of time series data.
• quantminer — Data/Pattern Mining Algorithms for Financial Data
• SeqCluPV — An extension of the original 'SeqClu' algorithm that is characterized by voting for cluster prototypes.
• signature-mahalanobis-knn — Using Nearest Neighbour-Variance Norm with Path Signatures for anomaly detection of streams
• sktime-dl — Deep learning extension package for sktime, a scikit-learn compatible toolbox for learning with time series data
• sphynxml — no summary
• stocktool — A tool for stock price visulization and forecasting
• taug — Time Series Forecasting and Data Augmentation using Deep Generative Models
• timely-beliefs — Data modelled as beliefs (at a certain time) about events (at a certain time).
• timemachines — Evaluation and standardization of autonomous time series prediction
• torchchronos — PyTorch and Lightning compatible library that provides easy and flexible access to various time-series datasets for classification and regression tasks
• torchtime — Benchmark time series data sets for PyTorch
• training-pipeline — no summary
• tsai — Practical Deep Learning for Time Series / Sequential Data library based on fastai & Pytorch
• tselect — Package for selecting the relevant and non-redundant channels for multivariate time series classification.
• tsfuse — Automated feature construction for multiple time series data
• TSInterpret — todo
• uea-ucr-datasets — A small package for loading and handling UEA UCR time series classification datasets.