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To prepare a model to predict whether the price of a particular share will go up or down in the following day.

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Stock-Market-Prediction-Model

CHAROTAR UNIVERSITY OF SCIENCE & TECHNOLOGY

DEVANG PATEL INSTITUTE OF ADVANCE TECHNOLOGY AND RESEARCH

Topic: Stock Market Prediction Model

Prepared By:

Rishik Karanjiya (18DIT023)

Dhaval Khunt (18DIT027)

Heet Pambhar (18DIT040)

Objective:

To prepare a model to predict whether the price of a particular share will go up or down in the following day.

Proposed Work Description:

To predict the stock market two data sets of a particular share has been considered i.e., price of the stock in previous year and price of the stock in previous month. The previous year data set is considered as the train data set and the previous month data set is considered as test data set. The algorithm in use is linear regression. The code is done so that it reduces the loss or error from the train data set and the result is implemented in the test data set to find the accuracy of the model.   Requirements:

• Pandas

• Numpy

• Tensorflow

Conclusion:

The linear regression model for stock market prediction is prepared and it wields a maximum accuracy of 62%.

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To prepare a model to predict whether the price of a particular share will go up or down in the following day.

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