Using Multi-Threading to Build Neural Networks with TensorFlow and Apache Spark

by Sophia TurolJuly 8, 2016


At the recent TensorFlow meetup in Paris, the attendees learnt how to construct neural networks employing the multi-threading approach. The topics under discussion also included distributed TensorFlow and the efficiency of using Apache Spark with TensorFlow.


TensorFlow and deep learning without a PhD

Martin Gorner of Google introduced the attendees to TensorFlow and taught how to choose the right neural network for a specific problem. He demonstrated how to train the network with just a couple of code lines and a bag of “tricks of the trade.”



Constructing neural networks using multi-threading

In his session, Maxence Queyrel of Quinten talked about multi-threading with TensorFlow and Apache Spark, highlighting:

  • Neural networks hyperparameters
  • How TensorFlow works with Apache Spark (examples, efficiency, etc.)
  • Distributed TensorFlow: What it is, how it works, and how to use it

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TensorFlow + Apache Spark

Jiqiong Qiu of SFEIR provided an overview of H2O—an open-source machine learning platform—explaining why and how to use it together with TensorFlow and Apache Spark. With H2O, users can get the best of Apache Spark (its APIs, RDD, simple context, multi-tenancy, etc.) and combine it with deep learning algorithms.


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Further reading


About the speakers

Martin Gorner is responsible for developer relations, working at Google (Paris, France). He is passionate about science, technology, coding, algorithms, and everything in between. He enjoyed his first engineering years in the computer architecture group of ST Microlectronics. Then, Martin spent 11 years shaping the nascent eBook market, starting with the Mobipocket startup, which later became the software part of the Amazon Kindle and its mobile variants.


Maxence Queyrel is a student in Master 2 of data science at Pierre et Marie Curie University. He is an intern at Quinten, where Maxence is a machine learner in charge of integrating TensorFlow into the company’s activities.



Jiqiong Qiu is a data scientist at SFEIR. She is master of engineer degree in Bioinformatic and modelization at INSA de Lyon. Jiqiong has also got a PhD in Color Formulation by Statistical Learning at UTC and BASF Coatings.
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