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prerequisites
basics of JavaScript • basics of HTML • basics of React • basics of TensorFlow.js • basics of machine learning and web development
skills learned
creating new modules within a React app • cleaning up the data • preparing data for training
Andrej Baranovskij
1 week · 4-6 hours per week · INTERMEDIATE
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Look inside
In this liveProject you’ll use human pose data and TensorFlow.JS’s PoseNet to build and train a machine learning model that can recognize workout exercises. This model will record and recognize the workout session of a user, to be logged for future comparison. You’ll need to prepare data structures for the TensorFlow.js Dataset API, and execute one-hot-encoding with a simple mapping function. You’ll also define model architecture using the TensorFlow.js sequential API, and train your model using the fitDataset method. You’ll finish up by saving your trained model in local browser storage to allow for model reuse.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Andrej Baranovskij
Andrej Baranovskij is a TensorFlow-certified developer who runs his own machine learning startup company Katana ML. Andrej is responsible for building machine learning products for enterprise operations automation. Previously, he spent 15 years working with Oracle technology and building various enterprise systems across the globe. His software development experience allows to bridge a gap between machine learning and software development.

prerequisites

This liveProject is for both web developers and machine learning engineers. Web developers experienced with JavaScript will learn how to integrate TensorFlow into their applications, while ML engineers will be interested in developing their skills for user interfaces.

TOOLS
  • Basics of JavaScript
  • Basics of HTML
  • Basics of Node.js, NPM, and Yarn
  • Basics of React
  • Basics of TensorFlow.js
  • Visual Studio Code
TECHNIQUES
  • Basics of machine learning
  • Basics of web development with HTML/JavaScript

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