click to
look inside
Look inside
End-to-End Deep Learning

Prepare Tabular Data

This project is part of the liveProject series End-to-End Deep Learning for Price Prediction.
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

placing your order...

Don't refresh or navigate away from the page.
try it! first milestone FREE
liveProject liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $19.99 $29.99 you save: $10 (33%) self-paced learning
FREE domestic shipping on orders of three or more print books
Prepare Tabular Data (liveProject) added to cart
continue shopping
go to cart
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.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

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

you will learn

In this liveProject, you’ll master all the skills you need to build a complete deep learning model and deploy it to production. You’ll get to grips with a common Python stack used for deep learning across numerous companies and industries.

  • Manipulate tabular data
  • Make geospatial visualizations
  • Use Keras to interface with TensorFlow
  • Adapt pipeline classes to encapsulate data preparation steps
  • Utilize Keras callbacks
  • Track and assess model performance
  • Create a web server with Flask
  • Serve deployment web pages

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
RECENTLY VIEWED