In this liveProject, you’ll create and train your deep learning model to predict where a new Airbnb listing will be priced above or below average pricing. You’ll put pandas, Keras, and scikit-learn into action, and master key deep learning techniques for tracking model performance. You’ll learn to harness callbacks in the Keras deep learning framework to make model training more efficient, and how to ensure consistent results in multiple training runs.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
This liveProject is for intermediate data scientists looking to expand their skill set with applied deep learning capabilities. To begin this liveProject, you will need to be familiar with:
- Intermediate Python
- Beginner pandas
- Beginner scikit-learn
- Beginner/Intermediate Keras
- Familiarity with Google Colab
- Familiarity with Jupyter Notebook
- Deep learning model layer assembly
- Deep learning model training
- Trained deep learning model one-off scoring
you will learn
In this liveProject, you’ll master powerful Python tools for training machine learning models. You’ll also learn useful Python concepts that will ensure that the application you build is robust and easy to maintain.
- Use Keras to interface with TensorFlow
- Adapt pipeline classes to encapsulate data preparation steps
- Utilize Keras callbacks
- Track and assess model performance