StockMarketML

This was one of our Machine Learning projects that was implemented in a team of 3 with equal contribution.

GOOG.CV - Contains the dataset of Google.com's stock market prices listed by Yahoo Finance

Stock_Market.ipynb - This contains the python notebook which has the main code of out project with a step by step implementation of machine learning algorithms as well as LSTM and the comparison between all of them on the basis of the predictions.

Stock_Price_Prediction_Report - This file is a detailed project report. It contains all the necessary information regarding our results, the methods we applied, several comparisons, and the details of references as well.

Poster for Presentation - This contains the poster that we made for presentng our project.

Contribution - Vaibhav Gaur gathered the dataset of Google’s Stock prices from Yahoo! Finance and preprocessed it so that unnecessary data can be cleaned and then implemented the Linear Regression on the data and concluded that it predicted the stock prices more accurately.

Shubham Sood did the data visualization and comparison graphs to see the pattern and trends in the data; after that, computation of training time needed for each algorithm is carried out, and the k-nn algorithm is applied to the data.

Lisha Uppal did the literature survey about the project so that we can get the knowledge about our project and we can explore about it then she applied Decision Tree algorithm and observed that it had the fastest execution time but takes the maximum time in training of the dataset moreover she made the proposal and report of the project.