ºÝºÝߣshows by User: mathieudumoulin2 / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: mathieudumoulin2 / Wed, 27 Sep 2017 11:05:19 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: mathieudumoulin2 Converged and Containerized Distributed Deep Learning With TensorFlow and Kubernetes /slideshow/converged-and-containerized-distributed-deep-learning-with-tensorflow-and-kubernetes/80211882 convergedandcontainerizedddlwithtfonkubernetesandmapr-170927110519
Docker containers running on Kubernetes combine with MapR Converged Data Platform allow any company to potentially enjoy the same sophisticated data infrastructure for enabling teams to engage in transformative machine learning and deep learning for production use at scale.]]>
Docker containers running on Kubernetes combine with MapR Converged Data Platform allow any company to potentially enjoy the same sophisticated data infrastructure for enabling teams to engage in transformative machine learning and deep learning for production use at scale.]]> Wed, 27 Sep 2017 11:05:19 GMT /slideshow/converged-and-containerized-distributed-deep-learning-with-tensorflow-and-kubernetes/80211882 mathieudumoulin2@slideshare.net(mathieudumoulin2) Converged and Containerized Distributed Deep Learning With TensorFlow and Kubernetes mathieudumoulin2 Docker containers running on Kubernetes combine with MapR Converged Data Platform allow any company to potentially enjoy the same sophisticated data infrastructure for enabling teams to engage in transformative machine learning and deep learning for production use at scale. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/convergedandcontainerizedddlwithtfonkubernetesandmapr-170927110519-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Docker containers running on Kubernetes combine with MapR Converged Data Platform allow any company to potentially enjoy the same sophisticated data infrastructure for enabling teams to engage in transformative machine learning and deep learning for production use at scale.
Converged and Containerized Distributed Deep Learning With TensorFlow and Kubernetes from Mathieu Dumoulin
]]> 2131 6 https://cdn.slidesharecdn.com/ss_thumbnails/convergedandcontainerizedddlwithtfonkubernetesandmapr-170927110519-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 State of the Art Robot Predictive Maintenance with Real-time Sensor Data /slideshow/state-of-the-art-robot-predictive-maintenance-with-realtime-sensor-data/78187842 stratabeijing2017-170724090220
Our Strata Beijing 2017 presentation slides where we show how to use data from a movement sensor, in real-time, to do anomaly detection at scale using standard enterprise big data software.]]>
Our Strata Beijing 2017 presentation slides where we show how to use data from a movement sensor, in real-time, to do anomaly detection at scale using standard enterprise big data software.]]> Mon, 24 Jul 2017 09:02:19 GMT /slideshow/state-of-the-art-robot-predictive-maintenance-with-realtime-sensor-data/78187842 mathieudumoulin2@slideshare.net(mathieudumoulin2) State of the Art Robot Predictive Maintenance with Real-time Sensor Data mathieudumoulin2 Our Strata Beijing 2017 presentation slides where we show how to use data from a movement sensor, in real-time, to do anomaly detection at scale using standard enterprise big data software. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/stratabeijing2017-170724090220-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Our Strata Beijing 2017 presentation slides where we show how to use data from a movement sensor, in real-time, to do anomaly detection at scale using standard enterprise big data software.
State of the Art Robot Predictive Maintenance with Real-time Sensor Data from Mathieu Dumoulin
]]> 1934 6 https://cdn.slidesharecdn.com/ss_thumbnails/stratabeijing2017-170724090220-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MapR and Machine Learning Primer /mathieudumoulin2/map-r-and-ml-primer maprandmlprimer-170724085944
MapR is an ideal scalable platform for data science and specifically for operationalizing machine learning in the enterprise. This presentations gives specific reasons why.]]>
MapR is an ideal scalable platform for data science and specifically for operationalizing machine learning in the enterprise. This presentations gives specific reasons why.]]> Mon, 24 Jul 2017 08:59:44 GMT /mathieudumoulin2/map-r-and-ml-primer mathieudumoulin2@slideshare.net(mathieudumoulin2) MapR and Machine Learning Primer mathieudumoulin2 MapR is an ideal scalable platform for data science and specifically for operationalizing machine learning in the enterprise. This presentations gives specific reasons why. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/maprandmlprimer-170724085944-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> MapR is an ideal scalable platform for data science and specifically for operationalizing machine learning in the enterprise. This presentations gives specific reasons why.
MapR and Machine Learning Primer from Mathieu Dumoulin
]]> 355 9 https://cdn.slidesharecdn.com/ss_thumbnails/maprandmlprimer-170724085944-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 CEP - simplified streaming architecture - Strata Singapore 2016 /slideshow/cep-simplified-streaming-architecture-strata-singapore-2016/69937172 kkwuqjbgqgov1secu9qw-signature-81c7438611a24048049f580a3cb5b9be8e3a4b0e2bb81a3d11f979530d990859-poli-161208025849
We describe an application of CEP using a microservice-based streaming architecture. We use Drools business rule engine to apply rules in real time to an event stream from IoT traffic sensor data.]]>
We describe an application of CEP using a microservice-based streaming architecture. We use Drools business rule engine to apply rules in real time to an event stream from IoT traffic sensor data.]]> Thu, 08 Dec 2016 02:58:48 GMT /slideshow/cep-simplified-streaming-architecture-strata-singapore-2016/69937172 mathieudumoulin2@slideshare.net(mathieudumoulin2) CEP - simplified streaming architecture - Strata Singapore 2016 mathieudumoulin2 We describe an application of CEP using a microservice-based streaming architecture. We use Drools business rule engine to apply rules in real time to an event stream from IoT traffic sensor data. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kkwuqjbgqgov1secu9qw-signature-81c7438611a24048049f580a3cb5b9be8e3a4b0e2bb81a3d11f979530d990859-poli-161208025849-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> We describe an application of CEP using a microservice-based streaming architecture. We use Drools business rule engine to apply rules in real time to an event stream from IoT traffic sensor data.
CEP - simplified streaming architecture - Strata Singapore 2016 from Mathieu Dumoulin
]]> 3923 8 https://cdn.slidesharecdn.com/ss_thumbnails/kkwuqjbgqgov1secu9qw-signature-81c7438611a24048049f580a3cb5b9be8e3a4b0e2bb81a3d11f979530d990859-poli-161208025849-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Streaming Architecture to Connect Everything (Including Hybrid Cloud) - Strata Singapore 2016 /mathieudumoulin2/streaming-architecture-to-connect-everything-including-hybrid-cloud-strata-singapore-2016 vmvelfturoomlz58yzs9-signature-9da52d9efb8e5b9568c91c7206c2d53e67b524e91d9bbc8531dba7e1b6a78094-poli-161207082822
Learn about what technologies enable a new, modern Stream-based architecture to connect everything within application modules or across data centers and public clouds. Combine Kafka-style streaming and stream processing frameworks like Spark and Flink with Microservices and completely rethink your big data architecture away from state and into data flows.]]>
Learn about what technologies enable a new, modern Stream-based architecture to connect everything within application modules or across data centers and public clouds. Combine Kafka-style streaming and stream processing frameworks like Spark and Flink with Microservices and completely rethink your big data architecture away from state and into data flows.]]> Wed, 07 Dec 2016 08:28:21 GMT /mathieudumoulin2/streaming-architecture-to-connect-everything-including-hybrid-cloud-strata-singapore-2016 mathieudumoulin2@slideshare.net(mathieudumoulin2) Streaming Architecture to Connect Everything (Including Hybrid Cloud) - Strata Singapore 2016 mathieudumoulin2 Learn about what technologies enable a new, modern Stream-based architecture to connect everything within application modules or across data centers and public clouds. Combine Kafka-style streaming and stream processing frameworks like Spark and Flink with Microservices and completely rethink your big data architecture away from state and into data flows. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/vmvelfturoomlz58yzs9-signature-9da52d9efb8e5b9568c91c7206c2d53e67b524e91d9bbc8531dba7e1b6a78094-poli-161207082822-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Learn about what technologies enable a new, modern Stream-based architecture to connect everything within application modules or across data centers and public clouds. Combine Kafka-style streaming and stream processing frameworks like Spark and Flink with Microservices and completely rethink your big data architecture away from state and into data flows.
Streaming Architecture to Connect Everything (Including Hybrid Cloud) - Strata Singapore 2016 from Mathieu Dumoulin
]]> 1234 4 https://cdn.slidesharecdn.com/ss_thumbnails/vmvelfturoomlz58yzs9-signature-9da52d9efb8e5b9568c91c7206c2d53e67b524e91d9bbc8531dba7e1b6a78094-poli-161207082822-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Real-World Machine Learning - Leverage the Features of MapR Converged Data Platform /slideshow/realworld-machine-learning-leverage-the-features-of-mapr-converged-data-platform/67756213 hadoopsummittokyo2016-161028021146
Examine the unique features of the MapR Converged Data Platform and how they can support production-grade enterprise machine learning - Ends with a live demo using H2O - Presented at Hadoop Summit Tokyo 2016]]>
Examine the unique features of the MapR Converged Data Platform and how they can support production-grade enterprise machine learning - Ends with a live demo using H2O - Presented at Hadoop Summit Tokyo 2016]]> Fri, 28 Oct 2016 02:11:46 GMT /slideshow/realworld-machine-learning-leverage-the-features-of-mapr-converged-data-platform/67756213 mathieudumoulin2@slideshare.net(mathieudumoulin2) Real-World Machine Learning - Leverage the Features of MapR Converged Data Platform mathieudumoulin2 Examine the unique features of the MapR Converged Data Platform and how they can support production-grade enterprise machine learning - Ends with a live demo using H2O - Presented at Hadoop Summit Tokyo 2016 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hadoopsummittokyo2016-161028021146-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Examine the unique features of the MapR Converged Data Platform and how they can support production-grade enterprise machine learning - Ends with a live demo using H2O - Presented at Hadoop Summit Tokyo 2016
Real-World Machine Learning - Leverage the Features of MapR Converged Data Platform from Mathieu Dumoulin
]]> 1326 2 https://cdn.slidesharecdn.com/ss_thumbnails/hadoopsummittokyo2016-161028021146-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Distributed Deep Learning on Spark /mathieudumoulin2/distributed-deep-learning-on-spark caffeonsparkmeetuptalk20160831-160901064559
Deep dive of SparkNet and comparison with CaffeOnSpark. Practical installation advice.]]>
Deep dive of SparkNet and comparison with CaffeOnSpark. Practical installation advice.]]> Thu, 01 Sep 2016 06:45:59 GMT /mathieudumoulin2/distributed-deep-learning-on-spark mathieudumoulin2@slideshare.net(mathieudumoulin2) Distributed Deep Learning on Spark mathieudumoulin2 Deep dive of SparkNet and comparison with CaffeOnSpark. Practical installation advice. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/caffeonsparkmeetuptalk20160831-160901064559-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Deep dive of SparkNet and comparison with CaffeOnSpark. Practical installation advice.
Distributed Deep Learning on Spark from Mathieu Dumoulin
]]> 1170 6 https://cdn.slidesharecdn.com/ss_thumbnails/caffeonsparkmeetuptalk20160831-160901064559-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Real world machine learning with Java for Fumankaitori.com /mathieudumoulin2/real-world-machine-learning-with-java-for-fumankaitoricom jjugccc2015fall-151128071940-lva1-app6892
For the Japan Java User Group Fall 2015 conference]]>
For the Japan Java User Group Fall 2015 conference]]> Sat, 28 Nov 2015 07:19:40 GMT /mathieudumoulin2/real-world-machine-learning-with-java-for-fumankaitoricom mathieudumoulin2@slideshare.net(mathieudumoulin2) Real world machine learning with Java for Fumankaitori.com mathieudumoulin2 For the Japan Java User Group Fall 2015 conference <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jjugccc2015fall-151128071940-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> For the Japan Java User Group Fall 2015 conference
Real world machine learning with Java for Fumankaitori.com from Mathieu Dumoulin
]]> 10675 8 https://cdn.slidesharecdn.com/ss_thumbnails/jjugccc2015fall-151128071940-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Introduction aux algorithmes map reduce https://fr.slideshare.net/slideshow/introduction-aux-algorithmes-map-reduce-35771176/35771176 introductionauxalgorithmesmapreduce-140611210400-phpapp02
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]]> Wed, 11 Jun 2014 21:04:00 GMT https://fr.slideshare.net/slideshow/introduction-aux-algorithmes-map-reduce-35771176/35771176 mathieudumoulin2@slideshare.net(mathieudumoulin2) Introduction aux algorithmes map reduce mathieudumoulin2 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductionauxalgorithmesmapreduce-140611210400-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br>
from Mathieu Dumoulin
]]> 1593 21 https://cdn.slidesharecdn.com/ss_thumbnails/introductionauxalgorithmesmapreduce-140611210400-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MapReduce: Traitement de données distribué à grande échelle simplifié https://fr.slideshare.net/slideshow/map-reduce-25466391/25466391 mapreduce-130821170205-phpapp01
Présentation qui reprend les éléments principaux de l'article fondamental sur MapReduce de Dean et Ghemawat de 2004: MapReduce: simplified data processing on large clusters]]>
Présentation qui reprend les éléments principaux de l'article fondamental sur MapReduce de Dean et Ghemawat de 2004: MapReduce: simplified data processing on large clusters]]> Wed, 21 Aug 2013 17:02:05 GMT https://fr.slideshare.net/slideshow/map-reduce-25466391/25466391 mathieudumoulin2@slideshare.net(mathieudumoulin2) MapReduce: Traitement de données distribué à grande échelle simplifié mathieudumoulin2 Présentation qui reprend les éléments principaux de l'article fondamental sur MapReduce de Dean et Ghemawat de 2004: MapReduce: simplified data processing on large clusters <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mapreduce-130821170205-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Présentation qui reprend les éléments principaux de l&#39;article fondamental sur MapReduce de Dean et Ghemawat de 2004: MapReduce: simplified data processing on large clusters
from Mathieu Dumoulin
]]> 2524 63 https://cdn.slidesharecdn.com/ss_thumbnails/mapreduce-130821170205-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Presentation Hadoop Québec https://fr.slideshare.net/slideshow/presentation-hadoop-qubec/25338108 presentationhadoopnofujitsu-130817094143-phpapp02
Introduction à Hadoop et à l'écosystème Hadoop. Remise en contexte et survol des concepts fondamentaux.]]>
Introduction à Hadoop et à l'écosystème Hadoop. Remise en contexte et survol des concepts fondamentaux.]]> Sat, 17 Aug 2013 09:41:43 GMT https://fr.slideshare.net/slideshow/presentation-hadoop-qubec/25338108 mathieudumoulin2@slideshare.net(mathieudumoulin2) Presentation Hadoop Québec mathieudumoulin2 Introduction à Hadoop et à l'écosystème Hadoop. Remise en contexte et survol des concepts fondamentaux. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentationhadoopnofujitsu-130817094143-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Introduction à Hadoop et à l&#39;écosystème Hadoop. Remise en contexte et survol des concepts fondamentaux.
from Mathieu Dumoulin
]]> 2981 11 https://cdn.slidesharecdn.com/ss_thumbnails/presentationhadoopnofujitsu-130817094143-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Introduction à Hadoop https://fr.slideshare.net/slideshow/introduction-hadoop/25337996 presentationhadoop0-130817093232-phpapp01
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]]> Sat, 17 Aug 2013 09:32:32 GMT https://fr.slideshare.net/slideshow/introduction-hadoop/25337996 mathieudumoulin2@slideshare.net(mathieudumoulin2) Introduction à Hadoop mathieudumoulin2 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentationhadoop0-130817093232-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br>
from Mathieu Dumoulin
]]> 4539 10 https://cdn.slidesharecdn.com/ss_thumbnails/presentationhadoop0-130817093232-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-mathieudumoulin2-48x48.jpg?cb=1571598688 If there is anything I am good at, it's the ability to understand a business problem and translate it into working, state of the art technology. I combine professional level skills of a big data architect, data engineer, machine learning engineer and data scientist. In Machine learning, Recently I've been working a lot with Hadoop (MapR's distribution) and Apache Spark, Apache Drill, Elasticsearch/Kibana and Kafka/MapR Streams for real-time event-driven processing. On the machine learning side, I have strong practical experience with supervised learning, especially applied to unstructured (text) data in English, Japanese and French. Within these data-related specialties, I am more of ... www.mapr.com https://cdn.slidesharecdn.com/ss_thumbnails/convergedandcontainerizedddlwithtfonkubernetesandmapr-170927110519-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/converged-and-containerized-distributed-deep-learning-with-tensorflow-and-kubernetes/80211882 Converged and Containe... https://cdn.slidesharecdn.com/ss_thumbnails/stratabeijing2017-170724090220-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/state-of-the-art-robot-predictive-maintenance-with-realtime-sensor-data/78187842 State of the Art Robot... https://cdn.slidesharecdn.com/ss_thumbnails/maprandmlprimer-170724085944-thumbnail.jpg?width=320&height=320&fit=bounds mathieudumoulin2/map-r-and-ml-primer MapR and Machine Learn...