Delve into deploying DL models on Android using TensorFlow Lite. Gain insights into training, converting models, and practical applications through case studies for efficient mobile integration.
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Course Overview
Traditionally, computationally intensive deep learning (DL) models aren’t deployed to mobile devices due to their limited memory and computational power. But with a lightweight framework such as TensorFlow (TF) Lite, DL models can be deployed and run efficiently on mobile and edge devices, benefiting from fast response time, data privacy, and cost reduction in cloud computing resources.
This course aims to equip you with the techniques to deploy DL models on Android devices using the TF Lite framework. Yo...Show More
Traditionally, computationally intensive deep learning (DL) models aren’t deployed to mobile devices due to their limited memory...Show More
WHAT YOU'LL LEARN
An understanding of Python libraries for data processing, analysis, visualization, and deep learning
The ability to apply TensorFlow and Keras to train deep learning models
Working knowledge of training and evaluating deep learning models on various datasets
The ability to convert TensorFlow models to the TensorFlow Lite format and deploy them to Android applications
An understanding of Python libraries for data processing, analysis, visualization, and deep learning
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TAKEAWAY SKILLS
Python 3
Deep Learning
Deep learning models in Keras
Course Content
83 Lessons1 Project10 Quizzes
1.
Getting Started with Python
7 Lessons
Learn how to use Python's core and collection data types, control flow, functions, file handling, and key libraries.
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