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Course Skill Level:


Course Duration:

2 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    AI / Machine Learning

  • Course Code:


Who should attend & recommended skills:

Those experienced in Python with basic IT & Linux skills seeking to build Android and iOS apps using TesnorFlow Lite & core ML

Who should attend & recommended skills

  • This course is geared for Python experienced developers, analysts or others with Python skills who want to build Android and iOS applications using TensorFlow Lite and Core ML.
  • Skill-level: Foundation-level Machine Learning skills for Intermediate skilled team members. This is not a basic class.
  • IT Skills: Basic to Intermediate (1-5 years’ experience)
  • Linux: Basic (1-2 years’ experience), including familiarity with command-line options such as ls, cd, cp, and su
  • Attendees without a programming background like Python may view labs as follow along exercises or team with others to complete them

About this course

Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this course will show you how to do so. The course starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Googles ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, compare its performance, and analyze the results on both mobile and cloud using TensorFlow Lite with an RCNN. By the end of this course, you will not only have mastered the concepts of machine learning but also learned how to resolve problems faced while building powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML.

Skills acquired & topics covered

  • Working in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:
  • Machine learning using classification, analytics, and detection tasks.
  • Working with image, text and video datasets to delve into real-world tasks
  • Building apps for Android and iOS using Caffe, Core ML and Tensorflow Lite
  • Demystifying the machine learning landscape on mobile
  • Age and gender detection using TensorFlow Lite and Core ML
  • Using ML Kit for Firebase for in-text detection, face detection, and barcode scanning
  • Creating a digit classifier using adversarial learning
  • Building a cross-platform application with face filters using OpenCV
  • Classifying food using deep CNNs and TensorFlow Lite on iOS

Course breakdown / modules

  • Machine learning basics
  • TensorFlow Lite and Core ML
  • TensorFlow Lite
  • Core ML

  • Age, gender, and emotion prediction
  • Convolutional Neural Networks
  • The implementation on iOS using Core ML

  • Artistic neural style transfer
  • Building the applications

  • ML Kit basics
  • Face detection
  • Barcode scanner
  • Text recognition

  • MobileNet models
  • Building the Android application

  • Generative Adversarial Networks
  • Understanding the MNIST database
  • Building the TensorFlow model
  • Training the neural network

  • Understanding face-swapping

  • Transfer learning
  • Training our own TensorFlow model