Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.

Overview

Stock Price Prediction Using Deep Learning

  • Univariate Time Series

Predicting stock price using historical data of a company using Neural networks for multi-step forecasting of stock price.

General info

This project is; to implement deep learning algorithms two sequential models of recurrent neural networks (RNNs) such as stacked LSTM, Bidirectional LSTM, and NeuralProphet built with PyTorch to predict stock prices using time series forecasting.

Table of contents

Visualising Stacked LSTM Result:

Screen Shot 2021-12-30 at 12 55 00 AM


Disclaimer

Attempts have been made to predict stock prices using time series analysis algorithms, but they are not yet available for betting in the real market. This is just a tutorial and implementation of deep learning models to forecast stock. Therefore, it is not intended to instruct people to buy stock from this repo.

Contact

Stock Price Prediction Using Deep Learning - feel free to contact!

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