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!
Note: 0/5 (0 notes) 247 students
Instructor(s): The Codex Initiative
Last update: 2022-10-10
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
- Just basic experience in Python and/or Java. The course provides a ground-up overview of Convolutional Neural Networks and their deployment.
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!
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
- Convolutional Neural Networks & Datasets
- Image Processing
- Training, Validation & Testing Datasets
- Neural Networks
- Convolutions & Filters
- Summary & Overview
- Quick Quiz
- Model Programming & Deployment
- Building CNNs: Python TensorFlow & Google Colab
- Colab Exercise
- Deploying CNNs to Android Studio
- Viewing Real Time AI Plant App! & Conclusion
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