Data Science
Build a model to predict stock market performance using LSTM
Analyse historical data on the stock market performance and apply the Long Short Term Memory (LSTM) Recurrent Neural Network model to predict the future prices of stock.
About this Menternship
Chitmonks, a Hyderabad based startup is digitising the versatile Chit fund to make it more transparent, trustworthy and efficient. Chit fund is a rotating saving scheme that has been a part of India’s financial system for more than a century now. However, this massive industry is largely informal. Chitmonks are changing that for the better by bringing technology into the equation. The company was started in 2016 with a vision to build a financially inclusive Bharat, one state at a time. They are the proud owners of the largest network of savings and borrowings chain powered by Blockchain in India. They understand that trust is crucial to any savings scheme and put it at the core of everything they build.

Stock market as an investment option is fast gaining momentum among millennials and gen z. Higher returns, easy liquidation, protection against liquidation and transparency are just some of the benefits it offers. However, it is far riskier than the conventional forms of investments. Good news is, stock prices can be predicted based on their past performance. Building machine learning models that predict future stock prices based on historical data adds significant value to investors.

By the end of this menternship, you will build a machine learning model that predicts future stock prices with a high degree of accuracy.
Why take up this Menternship?
On completing this Menternship, you will learn about
Applications of Data Science in the Stock Market
Predictions using RNNs

Data Wrangling
Model Building

A prediction Model using LSTM for predicting stock prices based on historical data.
Expected Output
  1. Report on Applications of Data Science in the Stock Market
  2. Python Notebook (Github/Kaggle) with properly commented codes + Markdown to explain each step as needed from the tasks of this component.
  3. Final Project Report on Model Building and Selection
  4. Submit your video
Build a model to predict stock market performance using LSTM
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