StockAnalysis-Stock Market Analysis and Prediction using Machine Learning algorithms.

Overview

• created a website which can predict following
  • HIGHEST values of a particular company
  • LOWEST values of a particular company
  • CLOSING values of a particular company
• Algorithms used:
  • Decision Tree Regression
  • Random Forest Regression
  • Support Vector Regression *Data taken from ** https://in.finance.yahoo.com/
• Use pandas-datareader package to connect to yahoo server to fetch dataframe

Resources Used:

Python: 3.7 Packages : pandas, pnadas-datareader, sklearn, numpy, requests, django, matplotlib, seaborn

Case Studies:

Model Building:

Initiallly, I connected to yahoo server using pandas-datareader package to fetch data of client defined duration(preffered : data of month or more).

Since data fetched is mostly numerical no need to clean data.

I started implementation with Linear Regression which in this case performs below expectations as can be seen in case studies.

After parameter tuning I figured out RandomForest, SVR and Decision Tree performs pretty well

Production:

In this step I thought of creating an interactive application for end user. After a lot thought I came up with developing website using django framework. Screenshots of website