Search Results for "machine learning python"

The Amazon Chime SDK for iOS makes it easy to add collaborative audio calling, video calling, and screen share viewing features to iOS applications by using the same infrastructure services that power meetings on the Amazon Chime service. This Amazon Chime SDK for iOS works by connecting to meeting session resources that you have created in your AWS account. The SDK has everything you need to build custom calling and collaboration experiences in your iOS application, including methods to:...

Posturr is a macOS application that uses computer vision and machine learning — specifically Apple’s Vision framework — to monitor a user’s posture in real time and encourage healthier habits by visually responding when poor posture is detected. Running locally on the Mac, the app accesses the built-in camera to detect when you slouch or sit incorrectly, and when it recognizes sustained slouching, it applies a progressive visual blur to the screen as a subtle but effective cue to straighten up. ...

...It was created for Xcode 8 and requires a physical iOS device because some examples use Metal. The project covers speech recognition, looped video playback, Live Photo capture, and audio volume fading. Its graphics and machine learning samples use Metal Performance Shaders for handwritten digit detection and real-time image recognition. Interface examples demonstrate UIViewPropertyAnimator, interactive blur progress, and 3D Touch preview interactions. It also includes image-rich local notifications, an iMessage sticker pack, and a simplified Core Data stack based on NSPersistentContainer. ...

...Either way, it just takes a few minutes. Bender suports the most common ML nodes and layers but it is also extensible so you can write your own custom functions. With Core ML, you can integrate trained machine learning models into your app, it supports Caffe and Keras 1.2.2+ at the moment. Apple released conversion tools to create CoreML models which then can be run easily. Finally, there is no easy way to add additional pre or post-processing layers to run on the GPU.

Machine Learning-based activity type detection. Improved detection of Core Motion activity types (stationary, walking, running, cycling, automotive). Distinguish between specific transport types (car, train, bus, motorcycle, airplane, boat). Optionally produce high level Path and Visit timeline items, to represent the recording session at human level.

Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the...