Analyzing and predicting the stock prices of Google using Artificial Recurrent Neural Network (RNN) architechture. This is a Regression problem.
This was made as a part of the project work for the course 15CSE481:Machine Learning and Data Mining Lab.
Because she is intelligent and likes to build new things with technology.
Model used: Long Short-Term Memory (LSTM)
Tools Used: TensorFlow, Keras, Numpy, Pandas, Matplotlib
Language used: Python
Project: Open the Jupyter Notebook, stock-price-prediction.ipynb