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A Stock Trend Prediction Web Application in Python. Here we will use Streamlit, an open-source Python library, that makes it easy to build custom web apps for Machine Learning and Data Science.

Step By Step Terminal Testing Output

Final Web Application Demo

Final Demo

Testing Retrieval Of Data

Retrieving

Testing Plotting Data

Plotting

Testing Plotting Our Moving Average 100

Notice how 'NaN appears for the first 100 rows, this is because we used a 100 day MA

Moving Average 100

Testing Plotting Our Moving Average's

Red is our 100MA and Green is our 200MA

Moving Average's

Splitting our Data 70/30, 70 for training 30 for testing

Splitting our Data

Summary of our Machine Learning Model

ML Model

Training our ML model Epochs

Training

Predicting our values and plotting them

Prediction

Demo for our Web app, showcasing the user input data display along with the data and time chart

Demo1

Demo for our Web app, showcasing the 100MA and 200MA

Demo2

Demo for our Web app, showcasing the future predictions

Demo3