Dennis Ig 's repositories
3D-ResNets-PyTorch
3D ResNets for Action Recognition (CVPR 2018)
account-financial-reporting
Financial reports for Odoo
AI-for-trading
Repository of all completed projects during the "AI for Trading" Nanodegree
awesome-ai-cancer
Awesome artificial intelligence in cancer diagnostics and oncology
awesome-darknet
Networks and Tools that are used to access and navigate on "darknets"
big-data-rosetta-code
Code snippets for solving common big data problems in various platforms. Inspired by Rosetta Code
cloudstate
Towards Serverless 2.0
Data-Science-Competitions
Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).
distage-example
Example project built with distage, tagless final and zio
DSFD-Pytorch-Inference
A High-Performance Pytorch Implementation of DSFD for Inference
generic-event-parser
This project is a Google Dataflow pipeline that process generic JSON messages from Google PubSub or Apache Kafka and writes it parsed to Google BigQuery.
Leetcode_company_frequency
Collection of leetcode company tag problems. Periodically updating.
LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
MarketData
MarketData
MICCAI-2019-Prostate-Cancer-segmentation-challenge
Medical Deep Learning 2D high resolution image segmentation project: MICCAI 2019 Prostate Cancer segmentation challenge
Pair-Trading-Reinforcement-Learning
An Structural Application of Reinforcement Learning in Pair Trading
scala-blockchain
Simple implementation of Blockchain in scala/akka for learning purposes
scalaomg-core
A Scala library for online multiplayer games
soft-tfidf
Mispelling tolerant tf-idf similarity metric
SparkDLTrigger
Notebooks with code and sample data for the blog article: "Machine Learning Pipelines for High Energy Physics Using Apache Spark with BigDL and Analytics Zoo"
stock_price_prediction
Predicting stock price movement using NN and XGBoost. Kaggle competition - Top 2% final standing.
strategy-fundamental
This strategy is based on fundamental indicators.
TradingGym
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
zio-graalvm-hello-world
zio graalvm hello world example app