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Deep Learning for Android Apps

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.

Intermediate

83 Lessons

16h

Certificate of Completion

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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This course includes

1 Project
147 Playgrounds
10 Quizzes
Course Overview
What You'll Learn
Course Content
Recommendations

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 and computational power. But with a lightweight framework such as TensorFlow (TF) Lite, DL models can be deployed and run effic...Show More

TAKEAWAY SKILLS

Python 3

Deep Learning

Deep learning models in Keras

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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Course Content

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.

2.

Machine Learning (ML) and Deep Learning (DL)

9 Lessons

Get started with machine learning principles, supervised/unsupervised learning, neural networks, and transfer learning for Android apps.

3.

TensorFlow (TF)

7 Lessons

Examine TensorFlow's framework, core APIs, constants, operations, graph building, and visualizing with TensorBoard.

8.

Image Classification Apps Using TF Lite

7 Lessons

Step through creating image classification apps using TF Lite models and Task Library on Android.

10.

Appendix

6 Lessons

Explore Kotlin essentials, from basics to advanced concepts like classes, lambdas, and generics.

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