Deep learning for predicting stock market prices and trends has become even more popular than before. I have used yahoo finance to collect the data and LSTM to build the stock trend model. I have streamlit to build web UI.

• numpy
• pandas
• matplotlib
• pandas_datareader
• scikit-learn
• tensorflow
• datetime
• streamlit

• fetch the data from start date to end date.
• choose the target variable (High or Low or Open or Close)
• create dataframe with input and variable.
• input is previous 10 days or 5 days stock price based on user choice.
• output is next day stock price.
• split the data into training and testing set.
• Scale the data input data.
• Build the LSTM model using keras module of tensorflow.
• Train the model using training data set.
• Save the model.

• Take user input (previous 10 days or 5 days stock price data).
• Scale the data.
• Load Saved model.
• Predict the Ouput