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Build AI Plant Classification App in Android (30 Minutes!)
Rating: 3.7 out of 5(51 ratings)
2,564 students

Build AI Plant Classification App in Android (30 Minutes!)

Learn how to build a plant classifying AI app in less than hour! Perfect intro to neural networks and mobile apps!
Created byThe Codex Initiative
Last updated 10/2022
English

What you'll learn

  • Define image processing and the dataset creation process
  • Create Convolutional Neural Network structures for datasets
  • Program Python neural networks on real-life datasets
  • Deploy machine learning models to mobile devices

Course content

2 sections • 10 lectures • 43m total length

  • Image Processing4:43

    Explore how images are used in Convolutional Neural Networks

  • Training, Validation & Testing Datasets6:01

    Explore the three different types of datasets in CNNs and supervised learning

  • Neural Networks4:25

    Explore the architecture of basic neural networks and classification models.

  • Convolutions & Filters5:15

    Explore how convolutions can be used as filters to bolster image features

  • Padding2:54

    Explore padding and how to increase features in an image.

  • Pooling4:08

    Explore pooling and effective data minimization techniques for CNNs.

  • Summary & Overview3:51

    Overview of key CNN topics needed for the hands-on programming component.

  • Quick Quiz

Requirements

  • Just basic experience in Python and/or Java. The course provides a ground-up overview of Convolutional Neural Networks and their deployment.

Description

This FREE course teaches students how to build an AI, plant classifying app from scratch in LESS THAN ONE HOUR!

  • In just one hour, you will have your own, fully-functioning AI app in your hands!


You'll learn the true theory behind Convolutional Neural Networks, while also understanding how to deploy ML models to mobile devices.


Topics covered include:

  • Dataset processing (i.e. images and pixel conversions)

  • Neural networks (how classification and layers work together)

  • Convolutions (filters to extract key image features)

  • Padding and Pooling (methods for data minimization and maximization)

  • Python ML model creation (using TensorFlow, GPUs, TPUs, and Google Colab software)

  • Deploying .tflite models to mobile devices

  • Testing results with actual samples, and next steps for mobile development!


The example covered in this course is for plants, but you can scale this code to ANY DATASET! This course teaches you to build a product you can actually use! At the end of the course, you will have an industry-level app in your hands! Just a few minutes!


Materials:

  • Computer/Laptop

  • Internet Connection

  • Google Account


This course is perfect for beginners to Python or data science, or those who are curious about general machine learning concepts. This course provides a rapid introduction to Convolutional Neural Networks, and provides the theory and programming knowledge to kickstart your AI career!

Who this course is for:

  • Python developers curious about data science

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