Statsmodels: statistical modeling and econometrics in Python
- python
- statistics
- econometrics
- data-analysis
Repository Index
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Fast and Accurate ML in 3 Lines of Code
A unified framework for machine learning with time series
- time-series
- machine-learning
- scikit-learn
- time-series-classification
A python library for user-friendly forecasting and anomaly detection on time series.
- python
- time-series
- forecasting
- machine-learning
Automatic extraction of relevant features from time series:
- data-science
- feature-extraction
- time-series
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.
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
- neocortex
- artificial-intelligence
- machine-intelligence
- hierarchical-temporal-memory
Probabilistic time series modeling in Python
- time-series
- deep-learning
- forecasting
- neural-networks
Lightning ⚡️ fast forecasting with statistical and econometric models.
- time-series
- statistics
- forecasting
- arima
NeuralProphet: A simple forecasting package
- forecasting
- time-series
- machine-learning
- fbprophet
STUMPY is a powerful and scalable Python library for modern time series analysis
- data-science
- time-series-analysis
- dask
- numba
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
- time-series
- time-series-forecasting
- deep-learning
- forecasting
Python AutoML toolkit for benchmarking classification, regression, and time-series forecasting models, with GPU acceleration, MLflow tracking, and automated preprocessing.
- machine-learning
- automl
- regression
- classification
An R package for causal inference in time series
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
- forecasting
- scikit-learn
- machine-learning
- python
Anomaly Detection and Correlation library
- anomaly-detection
- anomalydetection
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
- btc
- lstm
- rnn
- bitcoin
Tidy anomaly detection
- detect-anomalies
- decomposition
- iqr
- time-series
Metric anomaly detection
A portable C99 library of feature extraction functions for time series and other numeric data
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
- time-series-analysis
- model-selection
- bayesian-inference
- anomaly-detection
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.