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ml-mini-project's Introduction

ML-mini-project

STOCK PRICE PREDICTION

Made by: Yash Wadhwani - 65, Kushal Dayani - 67, Bhavesh Lalwani - 68 Our project focuses on predicting the close price of the stock.

Abstract

In Stock Market Prediction, the aim is to predict the future value of the financial stocks of a company. The recent trend in stock market prediction technologies is the use of machine learning which makes predictions based on the values of current stock market indices by training on their previous values. Machine learning itself employs different models to make prediction easier and authentic.

Approach

We have used Regression Analaysis and Time Series Prediction to predict the stock price values

Algorithms

Regression Analysis

In this model TSLA.csv file is used and Linear Regression and Decision Tree Regression is used. The performance metrics are calculated and compared. Using this model, if we know the opening price of stock today, it's hightest and lowest values of the previous day, volume of stocks sold yesterday, we can predict the closing price of the stock today.

LSTM Algorithm

In this model NSE-TATAGLOBAL.csv file is used as a training set and tatatest.csv is used as a test set. LSTM algorithm is used for stock price prediction.LSTM are powerful in sequence prediction problems as they have an ability to store past information.Also,here it is necessary as future stock price is predicted on the basis of past stock price.

ml-mini-project's People

Contributors

kushal-dayani avatar yashwadhwani08 avatar

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