George Paloulian's repositories
actor-framework
An Open Source Implementation of the Actor Model in C++
akka-log4j
Logging backend for Akka based on Log4j
araneae.reasoner
The core reasoner of the araneae project
babylon-kubeflow
Machine Learning Toolkit for Kubernetes
charts
Bitnami Helm Charts
araneae.deploy
Uses argocd to deploy all the necessary pieces for araneae into a Kubernetes cluster
compute-cluster
Akka Compute Cluster for various things in Scala
docker-janusgraph
Docker container images for JanusGraph.
docker-kaldi-gstreamer-server
Dockerfile for kaldi-gstreamer-server.
gst-kaldi-nnet2-online
GStreamer plugin around Kaldi's online neural network decoder
janusgraph-docker
Yet another JanusGraph, Cassandra and Elasticsearch in Docker Compose setup
kaldi-gstreamer-server
Real-time full-duplex speech recognition server, based on the Kaldi toolkit and the GStreamer framwork.
lithium
Lithium - A split-brain resolver for Akka-Cluster
logback-kafka-appender
Logback appender for Apache Kafka
saas-starter-kit
🔥 Enterprise SaaS Starter Kit - Kickstart your enterprise app development with the Next.js SaaS boilerplate 🚀
scalapy-numpy
Static facades for using NumPy in ScalaPy
StockPrediction
Plain Stock Close-Price Prediction via Graves LSTM RNNs
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
ta4j
A Java library for technical analysis.
Test-stock-prediction-algorithms
Use deep learning, genetic programming and other methods to predict stock and market movements