May 2021
Intermediate to advanced content level Intermediate to advanced
338 pages
7h 44m
English
Associated roles“By seeking and blundering we learn.”
—Johann Wolfgang von Goethe
You’re not limited to the models from TensorFlow Hub. Every day there are new and exciting models being tweeted, published, and highlighted in the community spotlight. These models and ideas are shared outside the Google-approved hubs, and sometimes they are even outside the realm of TensorFlow.js.
You’re starting to advance beyond the garden walls and work with models and data in the wild. This chapter is specifically geared toward arming you with new ways to make models from existing models, as well as charge you with the challenges of gathering and understanding data.
We will:
Introduce model conversion
Introduce Teachable Machine
Train a computer vision model
Review where training data comes from
Cover some key concepts of training
When you finish this chapter, you’ll be armed with a few ways of making a model and a better understanding of the process of using data to make a machine learning solution.
Out-of-Network Model ShoppingTensorFlow.js hasn’t been around for long. Consequently, the number of models available is limited, or at least there are fewer than other frameworks. That doesn’t mean you’re out of luck. You can often convert models that were trained on other frameworks to TensorFlow.js. Converting existing models to make new models that work in a new environment is a great way to find recently developed resources and create exciting and contemporary ...
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