Alternatives and similar repositories for power-laws-forecasting

Users that are interested in power-laws-forecasting are comparing it to the libraries listed below

• drivendataorg / power-laws-cold-start
  ☆23Updated last year
• ADGEfficiency / forecast
  a toolkit for forecasting energy time series
  ☆19Updated 3 years ago
• manujosephv / deeprenewalprocess
  GluonTS Implementation of Intermittent Demand Forecasting with Deep Renewal Processes arXiv:1911.10416v1 [cs.LG]
  ☆31Updated 3 years ago
• strongio / quantile-regression-tensorflow
  Tensorflow implementation of deep quantile regression
  ☆76Updated 2 years ago
• ceshine / quantile-regression-tensorflow
  Implementations of Quantile Regression
  ☆28Updated 6 years ago
• rakshita95 / DeepLearning-time-series
  LSTM for time series forecasting
  ☆28Updated 7 years ago
• drivendataorg / power-laws-optimization
  Example repository for the Power Laws: Optimizing Demand-side Strategies competition on DrivenData
  ☆28Updated last year
• drivendataorg / power-laws-anomalies
  ☆32Updated last year
• sintel-dev / Draco
  State space and deep generative models for time series.
  ☆54Updated last year
• buds-lab / building-prediction-benchmarking
  An array of open source ML models applied to long-term hourly energy prediction for institutional buildings
  ☆27Updated 3 years ago
• h3ik0th / ES_energy_Transformer
  Python Darts deep forecasting models
  ☆33Updated 3 years ago
• franck-durand / tsboost
  Time Series Forecasting Framework
  ☆41Updated 2 years ago
• shaypal5 / stationarizer
  Smart, automatic detection and stationarization of non-stationary time series data.
  ☆29Updated 2 years ago
• sakshi-mishra / solar-forecasting-RNN
  Multi-time-horizon solar forecasting using recurrent neural network
  ☆40Updated 4 years ago
• aqibsaeed / Entity-Embedding-with-LSTM-for-Time-Series
  Entity Embedding with LSTM for Time Series
  ☆30Updated 4 years ago
• jxx123 / fireTS
  A python multi-variate time series prediction library working with sklearn
  ☆94Updated 4 years ago
• CollinRooney12 / htsprophet
  Hierarchical Time Series Forecasting using Prophet
  ☆144Updated 4 years ago
• mloning / intro-to-ml-with-time-series-DSSGx-2020
  Python tutorial on machine learning with time series for DSSGx 2020
  ☆23Updated 4 years ago
• sachinruk / KerasQuantileModel
  Quantile Regression using Deep Learning. An alternative to Bayesian models to get uncertainty.
  ☆76Updated 7 years ago
• carlomazzaferro / scikit-hts-examples
  Example usage of scikit-hts
  ☆57Updated 2 years ago
• sarincr / Time-series-analysis-using-Python
  Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics…
  ☆33Updated 5 years ago
• Vishwacorp / nyc_uber_forecasting
  Forecasting Uber demand in NYC neighborhoods
  ☆34Updated 7 years ago
• LuisM78 / Appliances-energy-prediction-data
  Data sets and scripts for the publication in Energy and Buildings Data driven prediction models of energy use of appliances in a low-ener…
  ☆93Updated 8 years ago
• aybchan / uber-time-series
  Bayesian time series prediction
  ☆66Updated 4 years ago
• elena-roff / price-modeling-rf
  Data Analysis and Machine Learning with Python: EDA with ECDF and Correlation analysis, Preprocessing and Feature engineering, L1 (Lasso)…
  ☆32Updated 7 years ago
• cerlymarco / keras-hypetune
  A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.
  ☆61Updated 3 years ago
• Y-oHr-N / OptGBM
  Optuna + LightGBM = OptGBM
  ☆35Updated 2 years ago
• FilippoMB / Ensemble-Conformalized-Quantile-Regression
  Valid and adaptive prediction intervals for probabilistic time series forecasting.
  ☆94Updated 2 months ago
• dimitreOliveira / StoreItemDemand
  (117th place - Top 26%) Deep learning using Keras and Spark for the "Store Item Demand Forecasting" Kaggle competition.
  ☆25Updated 5 years ago
• pourya-ir / Medium
  ☆49Updated 5 years ago