Academics,
After School Class,
Coding,
Computers,
Engineering
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Description
This course enables students to learn tensorflow and build algorithms from scratch using Python. This course is specifically for building and training deep neural networks for image classification tasks. They will also learn how to tune and optimize neural networks. This course is ideal for high school students who want to use AI on images for innovative science projects, for those who want to build systems using computer vision and cameras, or anyone who wants to learn image classification using deep neural networks.
Topics, Tools, and Modules:
• Learn special types of Neural Networks, particularly Convolutional Neural Networks (CNN) and Residual Neural Networks (ResNet)
• Employ established patterns of these networks to build powerful image detection applications
• Gain expertise on how to tune Neural Networks and tuning parameters such as learning rate, numbers of layers, epochs and others.
• An introduction to Transfer Learning and how to use it effectively
• An introduction to GPUs and how GPUs help accelerate neural network training
• The students will build a custom project of their choice (note - if they are interested in participating in a competition, they are welcome to bring their project in for this class).
• Natural Images: Example, Category detection (Dog vs Cat etc). Emotion detection (Happy vs Sad).
• Scientific applications using medical images: example Cancer detection from histopathology images, diabetes detection from retinal images.
• Game applications using synthetic Images: Category detection (type of emoji etc).
• Use the same industry cloud tools that businesses and experts do (we heavily use Amazon Web Services AI tools), We show you how to use them easily. You can use the same tools as you do more classes.