Online or onsite, instructor-led live TensorFlow Lite training courses demonstrate through interactive hands-on practice how to use TensorFlow Lite to to deploy deep learning models on embedded devices.
TensorFlow Lite training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live TensorFlow Lite training can be carried out locally on customer premises in Lahore or in NobleProg corporate training centers in Lahore.
TensorFlow Lite is also known as Google's TensorFlow Lite.
NobleProg -- Your Local Training Provider
Lahore - Classroom
The Enterprise, Multan Road, Lahore, pakistan, 54500
For Sales Enquires and Meetings
Please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate office
This instructor-led, live training in Lahore (online or onsite) is aimed at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for Edge AI applications.
By the end of this training, participants will be able to:
Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
Develop and optimize AI models using TensorFlow Lite.
Deploy TensorFlow Lite models on various edge devices.
Utilize tools and techniques for model conversion and optimization.
Implement practical Edge AI applications using TensorFlow Lite.
This instructor-led, live training in Lahore (online or onsite) is aimed at engineers who wish to write, load and run machine learning models on very small embedded devices.
By the end of this training, participants will be able to:
Install TensorFlow Lite.
Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
Add AI to hardware devices without relying on network connectivity.
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