Reference no: EM133168246
Project - RNN Model
Assessment Description
The aim behind RNN is sequencing data, as well as determining the probability of an occurrence. Some common examples are chat boxes, generating image descriptions, and predicting or forecasting.
Complete the steps below, then write a comprehensive technical report as a Python Jupiter notebook (to include all code, code comments, all outputs, plots, and analysis). Make sure the project documentation contains a) problem statement, b) algorithm of the solution, c) analysis of the findings, and d) references.
1. Build a long short-term memory (LSTM) model to predict the price of stock for Apple for the year 2021.
2. Use 75 epochs.
3. Visualize the results for the LSTM model.
4. Evaluate your model by determining the root mean squared error and explain your results (how accurate is your model, what could you do to make it better, etc.).
5. See if the model can predict 2022 prices.
Summarize the overall functioning of the RNN and its accuracy.
While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.
Attachment:- Project.rar
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