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

This course includes

1 Project
147 Playgrounds
10 Quizzes

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

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

What You'll Learn

An understanding of Python libraries for data processing, analysis, visualization, and deep learning

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Course Content

1.

Getting Started with Python

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)

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

Customer Segmentation with K-Means Clustering

Project

3.

TensorFlow (TF)

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

Cats vs Dogs Classification with Convolutional Neural Networks

Project

4.

Dataset Processing Using TensorFlow

Break down complex ideas for efficient dataset handling using TensorFlow's tf.data API.
5.

Keras: High-Level TF API

Take a closer look at Keras APIs, model creation, layers management, training, and evaluation.

Diabetes Prediction Using Keras

Project

6.

Quick Start with Android Apps

10 Lessons

Follow the process of building, structuring, and managing components in Android apps.
7.

TensorFlow (TF) Lite

9 Lessons

Master deploying optimized deep learning models on mobile with TensorFlow Lite.
8.

Image Classification Apps Using TF Lite

7 Lessons

Step through creating image classification apps using TF Lite models and Task Library on Android.
9.

Object Detection Apps Using TF Lite

7 Lessons

Walk through building Android object detection apps using TF Lite and ML Kit.
10.

Appendix

6 Lessons

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

DL Model Using TF, Keras, and TF Lite

Project

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