Look inside
In this liveProject, you’ll deploy a pretrained basketball predictor deep learning model onto the web for easy use by clients. You’ll utilize the powerful TensorFlow.js framework to ensure the model works in the browser, as well as converting DataFrames into JavaScript arrays, and building a simple website around the model and data sets.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
prerequisites
This project is for intermediate Python programmers looking to enhance their data science skills with useful techniques for deploying deep learning. To begin this liveProject, you will need to be familiar with:
TOOLS
- Basics of Python
- Basics of pandas
- Basics of Google Colab
- Basics of TensorFlow and Keras
- Basics of HTML and JavaScript
TECHNIQUES
- Basics of machine learning
- Basics of web app development
you will learn
In this liveProject series, you’ll learn all the steps needed to deliver a working machine learning project to a client.
- Converting a model for use on the web with Python and TensorFlow
- Converting a trained network to H5 to use with TensorFlow.js
- Generate usable data sets accessible in JavaScript using pandas and NumPy
- Build a simple website with HTML and JavaScript