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Intelligent Mobile Application Development With Tensorflow

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Intelligent Mobile Application Development With Tensorflow

Last updated 1/2019
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.92 GB | Duration: 4h 0m

A practical guide to using TensorFlow and creating efficient Deep Learning models for your mobile apps

What you’ll learn
Learn the art of building models using pre-built models and scripts.
Use artificial intelligence in your models to build your first smart iOS/Android application.
Deploy TensorFlow models on iOS and Android platforms.
Design solutions to real-life computer vision problems.
Gain practical knowledge by coding TensorFlow models to solve real-life problems such as gesture or voice recognition
Transform your existing applications, while adding intelligent features to enhance their efficiency, using image recognition, object detection, and more.

Requirements
Basic mobile application development knowledge is assumed
Basic Machine Learning and TensorFlow knowledge would be an added advantage but isn’t a requirement.

Description
TensorFlow is one of the most popular deep learning frameworks available and can be used for solving real-world applications such as analyzing images, generating data, natural language processing, intelligent chatbots, robotics, and more. If you’re looking forward to building and deploying Machine Learning models on your mobile device with TensorFlow & TensorFlow Lite, then this is the perfect Course for you! This comprehensive 2-in-1 course is a practical, fast-paced guide to building smart mobile applications by applying Machine Learning features using TensorFlow & TensorFlow Lite. You’ll begin with learning the art of building models using pre-built models and scripts. You’ll use Artificial Intelligence in your models to build your first smart iOS/Android application. Moving further, you’ll gain practical knowledge by coding TensorFlow models and solve real-life problems such as gesture or voice recognition. Finally, you’ll create efficient Deep Learning models for your mobile apps and deploy TensorFlow models on mobile devices.By the end of this course, you’ll use TensorFlow to build mobile apps and add features to make your apps smarter. Apply Machine Learning models in real-time in mobile devices with the new and powerful TensorFlow Lite.Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Hands-On TensorFlow for Smart Application Development, covers TensorFlow to build mobile apps and add features to make your apps smarter. This course will show you how to develop smart applications the easy way using the power of TensorFlow and add intelligent features to make your applications smarter without delving into deep learning. You will begin by setting up the environment required to get started quickly followed by building and deploying your first machine model. Next, you will use TensorFlow Lite, which is well optimized for on-device machine learning. As we proceed further, you’ll get hands-on practice in building applications on different platforms such as iOS and Android. Lastly, you will get some crucial tips on how to make your existing applications smarter. By the end of the course, you’ll not only be comfortable with using TensorFlow for building applications but will also be able to integrate the power of artificial intelligence in your mobile apps.The second course, Hands-on TensorFlow Lite for Intelligent Mobile Apps, covers applying Machine Learning models in real-time in mobile devices with the new and powerful TensorFlow Lite. You will learn to implement smart data-intensive behavior, fast, predictive algorithms, and efficient networking capabilities with TensorFlow Lite. You will master the TensorFlow Lite Converter, which converts models to the TensorFlow Lite file format. This course will teach you how to solve real-life problems related to Artificial Intelligence—such as image, text, and voice recognition—by developing models in TensorFlow to make your applications really smart. You will understand what Machine Learning can do for you and your mobile applications in the most efficient way. With the capabilities of TensorFlow Lite, you will learn to improve the performance of your mobile application and make it smart. By the end of the course, you will have learned to implement AI in your mobile applications with TensorFlow.By the end of this course, you’ll use TensorFlow to build mobile apps and add features to make your apps smarter. Apply Machine Learning models in real-time in mobile devices with the new and powerful TensorFlow Lite.About the AuthorsSaikat Basak is currently working as a machine learning engineer at Kepler Lab, the research & development wing of SapientRazorfish, India. His work at Kepler involves problem-solving using machine learning, researching and building deep learning models. Saikat is extremely passionate about Artificial intelligence becoming a reality and hopes to be one of the architects of its future.Juan Miguel Valverde Martinez is a Deep Learning, Computer Vision and Tensorflow enthusiast, with an MSc in IT and Cognition from the University of Copenhagen. His main interests are Computer Vision and Medical Image Analysis, and he has recently been more interested in Adversarial Training and Natural Language Processing. In his free time, he likes to read papers and research. In addition to Computer Science, he also enjoys learning languages and cooking, especially the Mediterranean and Asian dishes.

Overview
Section 1: Hands-On TensorFlow for Smart Application Development

Lecture 1 The Course Overview

Lecture 2 What Are Smart Applications and Why Do We Want Them?

Lecture 3 Creating a Virtual Environment and Installing TensorFlow

Lecture 4 Building an Image Classifier with Eight Lines of Code

Lecture 5 Fast Image Recognition Using the TensorFlow API

Lecture 6 Training a Custom Image Recognition Model

Lecture 7 Deploying a TensorFlow Application Using Flask

Lecture 8 TensorFlow Image Classification on Android

Lecture 9 Artistic Style Transfer Using the TensorFlow API on Android

Lecture 10 Introduction to CoreML

Lecture 11 Supercharge Your Augmented Reality App with TensorFlow, CoreML, and ARKit

Lecture 12 TensorFlow for the Web – TensorFlow.js

Lecture 13 Text Classification – Predict the Movie Genre

Section 2: Hands-on TensorFlow Lite for Intelligent Mobile Apps

Lecture 14 The Course Overview

Lecture 15 Deep Learning

Lecture 16 Deep Learning Components

Lecture 17 TensorFlow

Lecture 18 TensorFlow Lite

Lecture 19 Hello World in TensorFlow

Lecture 20 Debugging Our Model

Lecture 21 Parameter Study

Lecture 22 Overfitting

Lecture 23 Deployment in iOS with TensorFlow Lite

Lecture 24 Introduction to the Problem and Dataset

Lecture 25 Developing the Handwriting Recognition Model

Lecture 26 Parameter Study

Lecture 27 Testing the Model

Lecture 28 Deployment in Android with TensorFlow Lite

Lecture 29 Data Augmentation

Lecture 30 Developing the Pattern Recognition Model

Lecture 31 Parameter Study and Data Augmentation

Lecture 32 Testing the Model

Lecture 33 Deployment in Android with TensorFlow Lite

Lecture 34 Introduction

Lecture 35 Developing the Gesture Recognition Model

Lecture 36 Parameter Study and Data Augmentation

Lecture 37 Adapting and Debugging the Model

Lecture 38 Deployment in Android with TensorFlow Lite

Lecture 39 Introduction

Lecture 40 Developing the Voice Recognition Model

Lecture 41 Dropout and Dataset Generation

Lecture 42 Deployment in Android with TensorFlow Lite

Lecture 43 Course Summary

Mobile Developers, Data Science Professional who want to make their mobile applications smart with TensorFlow to solve Machine Learning, Computer Vision or Deep Learning problems such as data prediction, visual or audio recognition, and more.


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