adwin5's repositories
deep_lip_reading
Code and models for evaluating a state-of-the-art lip reading network
adwin5.github.io
Adwin Jahn's page
ark-invest-api
API for tracking holdings and trades of ARK Invest funds
aws-5g-network-performance-analytics
Code to support the AWS Big Data Blog post Build a cloud-native network performance analytics solution on AWS for wireless service providers.
backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
balena-cam
Network Camera with Raspberry Pi and WebRTC. Tutorial:
balena-sensehat-example
Example of using the Pi, Sense-HAT, InfluxDB and Grafana
darkflow-for-NV-smart-city
modified version of darkflow to work for IEEE Nvidia smart city challenge
deck.gl
WebGL2 powered geospatial visualization layers
DeepRL
Combining deep learning and reinforcement learning.
developer-roadmap
Roadmap to becoming a web developer in 2018
docker-gitlab
Dockerized GitLab
facenet
Face recognition using Tensorflow
grademark
An API for backtesting trading strategies in JavaScript and TypeScript.
GraphSAGE
Representation learning on large graphs using stochastic graph convolutions.
IoT-data-simulator
Generic IoT data simulator. Provides possibility to replay datasets or generates data on fly. Supports various IoT platforms out of the box.
keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.
multicontainer-getting-started
Get up and running quickly with a multicontainer setup on balena
multiscale-yolo-scripts
The code is for IEEE Nvidia Smart city challenge (rank 4th in total)
React-Image-Viewer
Simple example of an image viewer/slider written in React
srslte-docker-emulated
Minimal end-to-end LTE. Dockerized and emulated radio over shared memory.
start_from_tensorflow_keras
Cool projects to start learning tensorflow and keras
tacker
Tacker: ETSI MANO NFV Orchestrator / VNF Manager. See https://wiki.openstack.org/wiki/Tacker
technicalindicators
A javascript technical indicators written in typescript with pattern recognition right in the browser