Statsmodels: statistical modeling and econometrics in Python
- python
- statistics
- econometrics
- data-analysis
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A python library for user-friendly forecasting and anomaly detection on time series.
- python
- time-series
- forecasting
- machine-learning
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
The machine learning toolkit for time series analysis in Python
- time-series
- timeseries
- time-series-analysis
- time-series-clustering
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
Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.
Easy to use .NET library for data and time series manipulation and for scientific programming
The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.
- cwt
- matlab
- cpp
- optimization
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
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
- feature-engineering
- machine-learning
- feature
- features
Streaming-first technical indicators with a Rust core: native Python, Node.js and WebAssembly bindings plus a C ABI hub for C, C++, C#, Go, Java and R. 514 indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement.
- algotrading
- backtesting
- bollinger-bands
- cryptocurrency
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.
Model your data with machine learning
- rubyml
- ml
- machine-learning
- machinelearning