At a Glance

Name: Predict stock prices with LSTM in PyTorch
Price: Free CAD
Rating: 4.5 (46 reviews)
Author: kang_wang, lucy_xu, ricky_shi, wojciech_fulmyk

Learn to predict time series data with Long Short-Term Memory (LSTM) in PyTorch. Create a deep learning model that can predict a stock's value using daily Open, High, Low, and Close values and practice visualizing results and evaluating your model. Build foundational skills in machine learning while exploring the LSTM architecture. Develop practical knowledge with this beginner-friendly tutorial and apply it to real-world datasets using PyTorch.

This beginner-friendly project helps you learn machine learning basics and the LSTM architecture. LSTM networks are particularly important for their ability to capture long-term dependencies and patterns in sequential data, making them ideal for time series prediction. You'll develop a model to predict stock prices, gaining practical experience in data preprocessing, model building, and training. Practice visualizing results and evaluating your model's performance, solidifying your ability to apply these techniques in real-world scenarios.

This hands-on project is based on the Build a recurrent neural network using Pytorch tutorial. The guided project format combines the instructions of the tutorial with the environment to execute these instructions without the need to download, install, and configure tools.

A look at the project ahead

By completing this project, you are able to:

Build an LSTM using PyTorch.
Train an LSTM model and evaluate the model with metrics such as mean squared error.

What you'll need

Basic to intermediate knowledge of Python: Familiarity with Python's core programming concepts and the ability to write and understand Python code.
An understanding of basic machine learning concepts: Although detailed explanations are provided, some prior knowledge of machine learning principles is beneficial.
An environment that supports Python: Everything is available in the JupyterLab, including any Python libraries and data sets.

Offered By: IBMSkillsNetwork

Predict stock prices with LSTM in PyTorch

At a Glance

A look at the project ahead

What you'll need

This Guided Project is part of the following Learning Paths