A python library for self-supervised learning on images.

MIT License

lightly

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

mljar-supervised


Description


Apple Configurator makes it easy to deploy iPad, iPhone, iPod touch, and Apple TV devices in your school or business.Use Apple Configurator to quickly configure large numbers of devices connected to your Mac via USB with the settings, apps, and data you specify for your students, employees, or customers.Apple Configurator features a flexible, device-centric design that enables you to configure one or dozens of devices quickly and easily. Simply select a single device or many at once and perform an action. With Apple Configurator, you're able to update software, install apps and configuration profiles, rename and change wallpaper on devices, export device information and documents, and much more. You can also inspect any device to see details like serial number and hardware addresses, which apps and profiles are installed, and its console log.Apple Configurator integrates with device enrollment and purchasing in Apple Business Manager or Apple School Manager to seamlessly distribute apps from the App Store. The all-new Prepare assistant makes it easy to supervise and configure a cart of iPads for the classroom or quickly enroll a large number of devices in your MDM server for ongoing management. The built-in configuration profile editor supports creating and editing profiles with the latest iOS settings.If youâre configuring devices in an environment where consistency is critical, Blueprints allow you to create a custom configuration for your devices that can be applied with one click. A Blueprint is a template device to which you add configuration profiles and apps and perform actions, just like you would to a connected physical device.Fully automate Apple Configurator and integrate its capabilities into your existing device management workflows using the included command-line tool, AppleScript scripting library, or Automator Actions.Support for iCloud Drive enables you to keep your configuration profiles and other settings consistent across multiple Configurator stations.




The Mobile App Pentest cheat sheet was created to provide concise collection of high value information on specific mobile application penetration testing topics.

MobileApp-Pentest-Cheatsheet

A cron like system built in Elixir, that you can mount in your supervision tree

cronex

Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation

Semi-Supervised Learning with Ladder Networks in Keras. Get 98% test accuracy on MNIST with just 100 labeled examples ! 

ladder_network_keras

K-nearest neighbors algorithm for supervised learning implemented in javascript

KNear

[DEPRECATED] Self-Supervised Extrinsic Calibration using 3D Spatial Transformer Networks

CalibNet

📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.