TensorFlow is Google’s groundbreaking open-source, machine learning platform: the more people use it, the smarter it gets. With 20 million developers in the world, Google tasked YML with increasing adoption through education resources anyone can use, anywhere.
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3Three of the first Google TensorFlow User Group (TFUG) certified people in the world were YML employees
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1mDevelopers have engaged with TensorFlow since YML’s engagement
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150,000Paid sign-ups for Machine Learning courses on Coursera and Udacity, designed by YML
Increase adoption of machine learning
Developers and business leads alike needed a way to clearly understand the impact of TensorFlow capabilities, while educating new students. Our challenge was to create a suite of mobile apps and tutorials that could be updated as the content evolved.
YML translated a complex topic like machine learning into something approachable and easy to navigate.
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Speech recognition
Explore an app that uses a microphone to spot keywords in natural language. Can be used for voice-based interfaces, as well as keyword recognition and advanced learning in classrooms.
See the code -
Object Detection
Recognize different objects in an image, using a pre-trained model. Can be used for image and object-based search, or manufacturing-line quality control.
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Image Recognition
Test an image with a pre-trained model that can recognize 1,000 different types of items. Can be used for image and object-based search, or manufacturing-line quality control.
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Gesture recognition
Develop and train a neural network to recognize hand gestures. Can be used for touch-less interfaces — E.G. surgeons, machine operators, even gesture-based authentication.
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Getting demos in developers hands
Experience is the best teacher. YML built a series of dynamic tutorials (coursework, tools, machine learning applications) that proved to reach developer and business audiences alike.
“We could not have done this work at the same speed and efficiency as the YML team.”
Technology Architecture
We had the opportunity to create tutorials for Google’s Tensorflow ecosystem. For each of the blocks below we showcased the intricacies of that technology, and also how to work with all components together, effectively teaching students how the applications are built from training to deployment.
How we did it
Strategy
- Content Strategy
- Product Strategy
- Research
- User Testing
Content
- Course Structure Development
- Course Slides
- Class Exercises
Design
- Visual design
Engineering
- Machine Learning
- Proof-of-concept
- Prototyping
- Front-End and Back-End Development
