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Avoid Bottlenecks in distributed Deep Learning pipelines with Horovod
Categories: Data Science | Tags: GPU, Deep Learning, Horovod, Keras, TensorFlow
The Deep Learning training process can be greatly speed up using a cluster of GPUs. When dealing with huge amounts of data, distributed computing quickly becomes a challenge. A common obstacle which…
By Grégor JOUET
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Applying Deep Reinforcement Learning to Poker
Categories: Data Science | Tags: Algorithm, Gaming, Q-learning, Deep Learning, Machine Learning, Neural Network, Python
We will cover the subject of Deep Reinforcement Learning, more specifically the Deep Q Learning algorithm introduced by DeepMind, and then we’ll apply a version of this algorithm to the game of Poker…
Jan 9, 2019

Apache Metron in the Real World
Categories: Cyber Security, DataWorks Summit 2018 | Tags: Algorithm, NiFi, Solr, Storm, pcap, RDBMS, HDFS, Kafka, Metron, Spark, Data Science, Elasticsearch, SQL
Apache Metron is a storage and analytic platform specialized in cyber security. This talk was about demonstrating the usages and capabilities of Apache Metron in the real world. The presentation was…
May 29, 2018

Scaling massive, real-time data pipelines with Go
Categories: Open Source Summit Europe 2017, Learning | Tags: Algorithm, Data structures, Go Lang, Pipeline, Protocols, Network
Last week at the Open Source Summit in Prague, Jean de Klerk held a talk called Scaling massive, real-time data pipelines with Go. This article goes over the main points of the talk, detailing the…
Nov 21, 2017

Definitions of machine learning algorithms present in Apache Mahout
Categories: Data Science | Tags: Algorithm, Сlassification, Hadoop, Mahout, Clustering, Machine Learning
Apache Mahout is a machine learning library built for scalability. Its core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop…
By David WORMS
Mar 8, 2013