Egor's repositories
VegaScroll
VegaScroll is a lightweight animation flowlayout for UICollectionView completely written in Swift 4, compatible with iOS 11 and xCode 9.
Alerts-Pickers
Advanced usage of UIAlertController with TextField, DatePicker, PickerView, TableView and CollectionView.
avs-device-sdk
An SDK for devices to interface with the Alexa Voice Service and bring intelligent voice to any connected device.
awesome-remote-job
A curated list of awesome remote jobs and resources. Inspired by https://github.com/vinta/awesome-python
binance-trade-bot
Automated cryptocurrency trading bot
CryptoSwift
CryptoSwift is a growing collection of standard and secure cryptographic algorithms implemented in Swift
EFResume
Emmmmmn, a normal resume templete in Swift.
expanding-collection
ExpandingCollection is a card peek/pop controller
FaceRecognition-in-ARKit
Detects faces using the Vision-API and runs the extracted face through a CoreML-model to identiy the specific persons.
houdini-public
Houdini for iOS
LicenseGenerator-iOS
Xcode build script that recursively searches for LICENSE files and generates a Settings.bundle friendly plist.
MCScratchImageView
A custom ImageView that is used to cover the surface of other view like a scratch card, user can swipe the mulch to see the view below.
Mind-Expanding-Books
:books: Books that will blow your mind
SeeFood
Inspired by HBO's Silicon Valley: SeeFood is an iOS app that uses CoreML to detect various dishes
SheetKit
A lightweight and user-friendly Swift library to create modern, adaptive, card styled UI for action sheet and interactive bottom sheets easily.
Shuffle
🔥 A multi-directional card swiping library inspired by Tinder
TelegramSwift
Source code of Telegram for macos on Swift 4.0
tensorflow-build
A set of scripts to (cross-)build the Tensorflow C lib for various architectures / OS
torch2coreml
Torch7 -> CoreML
TransmogrifAI
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning