This is the Linux app named Stock prediction deep neural learning whose latest release can be downloaded as v1.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Stock prediction deep neural learning
DESCRIPTION
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock prices is a complex task, as it is influenced by various factors such as market trends, political events, and economic indicators. The fluctuations in stock prices are driven by the forces of supply and demand, which can be unpredictable at times. To identify patterns and trends in stock prices, deep learning techniques can be used for machine learning. Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that is specifically designed for sequence modeling and prediction.
Features
- Creation of the deep learning model LSTM
- Data Normalization
- Add Timesteps
- Training and Validation Data
- Make predictions happen
- Built using Python 3.10 version
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/stock-prediction-deepnl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
