Prepare Tabular Data

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prerequisites
intermediate Python • basics of pandas • basics of Folium
skills learned
manipulate tabular data • create geospatial visualizations
Mark Ryan
1 week · 10 hours per week · INTERMEDIATE
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Look inside
In this liveProject, you’ll use the Python tools pandas and Folium to prepare the Airbnb dataset for training a deep learning model. You’ll learn Python concepts that ensure the application you build on this data is robust and maintainable, and implement geospatial and visualization techniques to illustrate the geographic distribution of Airbnb rentals.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Mark Ryan
Mark Ryan has a Bachelor in Computer Science from the University of Waterloo and an MSc in Computer Science (with a specialty in Artificial Intelligence) from the University of Toronto. As a senior leader for IBM's Db2 relational database, he was immersed in structured, tabular data. Mark is currently a Data Science Manager at Intact Insurance. In addition to deep learning, Mark's interests include chatbots and transformer-based language models.

prerequisites

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:

TOOLS
  • Intermediate Python
  • Basics of pandas
  • Basics of Folium
  • Basics of Flask
  • Basics of scikit-learn
  • Basics of Keras
  • Basics of Ngrok
  • Basics of Google Colab
  • Basics of Jupyter Notebook
  • Basics of HTML, CSS, and JavaScript
TECHNIQUES
  • Deep learning model layer assembly
  • Deep learning model training
  • Trained deep learning model one-off scoring
  • Invoking deep learning models
  • Basics of web development

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