3D Neural Network Visualization with TensorSpace [Video]

More Information
  • Prepare a pre-trained model for visualization from numerous neural network libraries like Keras, TensorFlow and Tensorflow.js.
  • Explore how each part of your neural network model is presented and learn how to change it
  • Discover the inner-workings of your pre-trained model using a specific example in an easy and accessible way
  • Develop new insights by looking at your neural network from a fresh perspective
  • Discover how to easily present and explain your neural network architectures.

TensorSpace is a neural network 3D visualization framework built by TensorFlow.js, Three.js, and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser.

By applying TensorSpace API, it is more intuitive for Data Scientists to visualize and understand any pre-trained models built by TensorFlow, Keras, TensorFlow.js, and so on.

In this quick and short course, you’ll learn how to present the inner workings of your pre-trained Neural Network models with easy-to-access 3D visualizations in a web browser.

By the end of this course, you’ll be able to create compelling 3D visualizations that will show the neural network architecture and how pre-trained models work in real time with TensorSpace

The code bundle for this video course is available at - https://github.com/PacktPublishing/3D-Neural-Network-Visualization-with-TensorSpace

Style and Approach

In this course we seamlessly mix the theory with practice, to make your learning experience effective and enjoyable.

  • Prepare pre-trained models from a variety of neural network libraries for 3D visualization
  • Discover how to present the architecture of your neural network
  • Explore ways to show how your pre-trained neural network models work with example data in real-time
Course Length 55 minutes
ISBN 9781838642105
Date Of Publication 30 Mar 2019


Jakub Konczyk

Jakub Konczyk has enjoyed and done programming professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share it with others. He first discovered Machine Learning when he was trying to predict the real estate prices in one of the early-stage start-ups he was involved in. He failed miserably. Then he discovered a much more practical way to learn Machine Learning that he would like to share with you in this course. It boils down to “Keep it simple!” mantra. Kuba is an author of multiple bestselling video courses on Machine Learning and Deep Learning including Real-World Deep Learning Python Projects and AI in Finance.