Suitable for students in Middle School and High School (Grades 6-12)
This course is ideal for students who want to learn Tensorflow for advanced deep learning algorithms that are used in computer vision and cameras.
Anyone who is familiar with python and AI basics (or) has taken Deep Learning & Image Classification (M3) and Python with AI (PA1) is suitable for taking this class. AI Basics shows students what AI is and how to use it, while M2 introduces students to KNN and Linear Regression. In this class, students learn the internals of powerful deep learning algorithms. They learn how to code from scratch in Tensorflow.
Learn Artificial Intelligence - a new technology that is shaping our world!
Students enrolling are expected to have an introductory deep learning class in images (M3 or Summer Camp) and basic python background, which could be an entry-level python course with us (PA1 or Summer Camp).
Why learn TensorFlow?
Python is a language in very high demand because of its versatility and penetration into just about every industry. TensorFlow, built by Google, is a state-of-the-art deep learning platform. Image classification within deep learning is the Artificial Intelligence field that deals with images, be it natural, synthetic, or medical. Automated processing of images is used widely everywhere in the real world for reducing human labor and subjectivity.
Why join our AIClub Summer Camp?
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Designed and taught by PhDs and AI Experts
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Proven - hundreds of K-12 students have built custom projects. Some have won STEM and Innovation competitions
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Only workshops where students can build Python-powered AIs and publish them online! Students love building AIs and learning how they work
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Fun! Students build many programs and complete a project of their choice.
Please see our brochure for more info about our programs!
Description
• Introduction to Tensorflow
• Learn special types of Neural Networks, particularly Convolutional Neural Networks (CNN) and MobileNetV2 and how to code them from scratch.
• Employ established patterns of these networks to build powerful image detection applications
• 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.
• 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.
What Students Take Away
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Review of core programming concepts - flowcharts, input/output, loops, conditionals, data structures. Introduction to data preparation mechanisms for image data
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Transfer Learning - how to transfer the learning of a state-of-the-art model for your own custom data. How to process large amounts of data by splitting the TensorFlow pipelines.
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How to combine Python, Image Data Preparation and Deep Learning to create an intelligent app that can communicate with users and classify images.
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Build a custom Image Processing project and application in Python.
Schedule
Duration: 5 sessions / 3 hours per session
We offer a range of dates and times to accommodate busy schedules.
Also - note that since we use entirely online tools, if a student must miss a class, it is easy for them to do the required work at home. We provide materials for missed classes. We do ask however that the student attend the first and last class since this is needed for them to get oriented and also complete their custom project.