( under development , not ready for production , looking for contributors )
Predictoo is a python package which allows to predict the future of a time series.Predictoo contain 10 deep learning model .It is a tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. It is based on an additive model where non-linear trends are fit with yearly and weekly seasonality, plus holidays. It works best with time series that have strong seasonal effects and several seasons of historical data.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
The things you need before installing the software.
- python 3.6 or higher
- tensorflow 2.0 or higher
A step by step guide that will tell you how to get the development environment up and running.
bash
$conda create -n predictoo python=3.6
$pip install -r requirements.txt
ollah your good to go
config the cofig.py accordingly to your training enviroment . Predictoo requre dataset ['Date','Open', 'High', 'Low', 'Close', 'Volume',] following formate .
for every time serice data there is a simple preprocessing pipeline which will formate your date and split the data into test , train inside the aftifact folder
dataset_path: must reset according to your dataset dir
model_path: must reset with a dir where you want to store your train weights
$ python data_injections.py
bash
$ cd src/components
$ python model_train.py -p 14 -f 1
model evaluation
$ python model_evaluation.py