Learn

• 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.

About

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.

Features

• 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