Name: Giuseppe Bonaccorso
Type: User
Company: Artificial Intelligence, Machine Learning, Data Scientist
Bio: I am Head of Data Science with wide experience in Artificial Intelligence, Machine Learning and Data Science project design, management, and delivery.
Twitter: GiuseppeB
Location: Italy
Blog: https://www.bonaccorso.eu
Giuseppe Bonaccorso's Projects
Original Apollo 11 Guidance Computer (AGC) source code for the command and lunar modules.
A packaged and slightly-modified version of https://github.com/bbitmaster/ale_python_interface
Deep Learning and deep reinforcement learning research papers and some codes
Official mirror of the AWS SDK for Java. For more information on the AWS SDK for Java, see our web site:
Bayesian Python: Bayesian inference tools for Python
BBC News classification algorithm comparison
AWS SDK for Python
Caffe: a fast open framework for deep learning.
COCO API - Dataset @ http://cocodataset.org/
Open Source Web Crawler for Java
The Open Images dataset
A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility
Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)
ECIES implemented in Go
A text file containing 355k English words
FST: fast java serialization drop in-replacement http://ruedigermoeller.github.io/fast-serialization/
Modern & flexible browser fingerprinting library, a successor to the original fingerprintjs
Fundamentals of Machine Learning with Scikit-Learn
A toolkit for developing and comparing reinforcement learning algorithms.
Automated integer hash function discovery
A Java HTTP client for consuming Twitter's Streaming API
Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.
A working implementation of JSONB support on a Java + Hibernate application.
Python app used to download image sets using ImageNET links.
Generates thymeleaf templates for JPA entities
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.
Deepdream experiment implemented using Keras and VGG19 convnet