Introduction to TensorFlow Lite is about tools for on-device machine learning to run models on devices for better connectivity & lower power consumption.
Introduction to TensorFlow Lite Certification teaches how to deploy (DL) deep learning models on mobile and embedded devices with TensorFlow Lite. It includes various programming languages support such as Java, Swift, Objective-C, C++, and Python.
Introduction to TensorFlow Lite Classes is developed by the TensorFlow team and Udacity together as a practical approach to model deployment for software developers. All candidates get hands-on experience with the TensorFlow Lite framework as you deploy deep learning models on Android, iOS, and even an embedded Linux platform.
By the end of this Introduction to TensorFlow Lite Training, all candidates will have the skills necessary to start deploying their own deep learning models into mobile apps.
Introduction to TensorFlow Lite Certification Course is designed for aspirants who want to learn TensorFlow Lite to execute efficiently on most devices with limited compute and memory resources. All students after completion of classes get Introduction to TensorFlow Lite Certification by Udacity.
Introduction to TensorFlow Lite Certification Fees is nil that is it is free of cost.
Description
Amount (In INR)
Course Training Total Fee
Nil
No
This course is designed especially for those students who want to learn TensorFlow Models that perform at low latency. Light-weight and low latency models can be achieved by reducing the amount of computation required to predict. There will be ample job opportunities if relevant people choose this course such as:
Educational Qualification
The Introduction to TensorFlow Lite Classes is open to everyone interested to learn TensorFlow Lite. One should have some Python Certification Course Experience or General Experience in with the TensorFlow Lite framework.
Students enrolled in this course learn about TensorFlow Lite which is an open-source, cross-platform deep learning framework or platform that converts a pre-trained model in TensorFlow to a special format which in turn can be optimized for speed or storage as per the requirements.This special format model can be deployed on any edge devices like smartphones that run on Android or iOS or Linux based embedded devices like example of a single-board computer Raspberry Pi or Microcontrollers to make the presumption inference at the Edge Devices.
All students will be capable of performing these after completion of Introduction to TensorFlow Lite Online Course:
The admission for the certificate course in Introduction to TensorFlow Lite starts soon for limited seats only. Interested candidates are requested to enroll as soon as possible by following the steps mentioned below:
Step 1: Open the form on Udacity website (https://auth.udacity.com/)
Step 2: Fill in the necessary details
Step 3: Upload documents
Step 4: Wait for Confirmation
Introduction to TensorFlow Lite Certification Benefits students by learning into Deep Learning models at the Edge that make faster inferences irrespective of network connectivity that can be further learned with Neural Network With Tensorflow Certification Courses. Such models that are deployed on the Edge device are secure, that is no data leaves the device or is shared across the network, hence there is no concern for data privacy, learning this course helps you build and apply your own deep neural networks to produce amazing solutions to important challenges.
Mr Daniel Situnayake Developer Advocate Google
Ms Paige Bailey Developer Advocate Google
Mr Juan Delgado Content Developer Udacity
Other Masters, Ph.D
The major difference between TensorFlow Lite and TensorFlow is that it is the next version of TensorFlow and applications developed on TensorFlow Lite will have better performance and less binary file size than TensorFlow.
The Classes for this certification course by Udacity are conducted online.
TensorFlow Lite enables on-device machine learning by helping software developers run their models on mobile or edge devices.
TensorFlow Lite is an open-source, product ready and cross-platform deep learning framework.
Daniel Situnayake, Paige Bailey and Juan Delgado is the Instructor from Udacity for this online course
Yes. You can be sure that learning this skill will be worth your time and effort, especially if you want a high-paying job.
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