Learn how to build pose detection deep learning iPhone app

About this course

Course DescriptionLearn to build real time pose detection iPhone app using Posenet deep learning algorithm.  Deep learning is popular where a machine can be trained to detect poses in video and images.  Once trained, it can be used to detect poses in any video or image. The app does not require any wifi or cellular connectivity.  It uses deep learning and pretrained posenet model. It leverages apple's coreml and vision SDK to achieve pose detection entirely on the phone. Since the app does not send your images or vides to remote service, it maintains your privacy and data secured. Build a strong foundation in pose detection engines  with this tutorial for beginners.Understanding fundamentals of pose detectionUnderstanding fundamentals of deep learning and CNN Benefits of posenet for fitness appsBuild a real life pose detection in video using posenet, computer vision, coreml and swiftBuild a real life pose detection in image  using posenet, computer vision,, coreml and swiftA Powerful Skill at Your Fingertips  Learning the fundamentals of real time pose detection  puts a powerful and very useful tool at your fingertips. swift, posenet and coreml are free, easy to learn, has excellent documentation.No prior knowledge of CNN or deep learning is assumed. I'll be covering topics like CNN from scratch. Jobs in computer vision area are plentiful, and being able to learn real time object detection will give you a strong edge. YOLO is  state of art technology that can quickly help you achieve your goal. Learning pose detection with posenet will help you become a computer vision developer which is in high demand.Content and Overview  This course teaches you on how to build real time pose

Course objectives

• equip students with knowledge of deep learning concepts
• enable students to create a functioning iPhone app that utilizes pose detection technology
• emphasize data security in app development