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Machine learning ‘Linear regression’ and ‘Neural Network’ algorithms are used to predict the closing price of the stock by analyzing the opening price.

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Stock-Price-Prediction-System

In Machine learning algorithms like ‘Linear regression’ and ‘Neural Network’ are used to predict the closing price of the stock by analyzing the opening price and the relative trend of that particular stock.

Linear Regression

Linear Regression is a machine learning algorithm based on supervised learning. It performs a regression task. Regression models a target prediction value based on independent variables. It is mostly used for finding out the relationship between variables and forecasting. Different regression models differ based on – the kind of relationship between dependent and independent variables, they are considering and the number of independent variables being used.

Neural Networks

Neural networks are a class of machine learning algorithms used to model complex patterns in datasets using multiple hidden layers and non-linear activation functions. A neural network takes an input, passes it through multiple layers of hidden neurons (mini-functions with unique coefficients that must be learned), and outputs a prediction representing the combined input of all the neurons.

How to run

1.fork and then clone or just simply download zip file
2.Open spyder IDE
3.Set the current directory to the directory where code is downloaded
4.Open the code
5.Click on Run

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Machine learning ‘Linear regression’ and ‘Neural Network’ algorithms are used to predict the closing price of the stock by analyzing the opening price.

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