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the event program speakers contact & access sponsors videos & slides about us code of conduct fr videos the data centric conference in paris dataxday is a technical conference for enthusiasts and professionals from the world of data. big or small data, real-time or batch processing, classical machine learning or deep learning… as developers these are some of the core subjects that keep us up at night. are you a data pro ? come listen to experts who work on data exploitation and related technologies. 200 attendees come and meet more than 200 data lovers like yourself and let's talk data! for developers and tech leads our goal is to dive deeply into some of the hottest technical subjects at the crossroad between data science, data engineering, cloud computing, craftsmanship and security. one day on may 17th, spend your day enjoying talks from renowned speakers and sharing your ideas on what the future holds. dataxday will cover the following topics: data science: the next chapter being convinced by the benefit of data science, companies have started to integrate it in their workflows. the new challenge is to maintain, deploy and improve them. what is the future of data science in terms of methods and their implementation in production? streaming: data in motion in addition to dealing with large amounts of information, there is an increasing demand for real time data analysis. fast data is driving the field of data engineering. what are the technologies and patterns of the next reliable and efficient data pipelines? big data architecture essentials not that long ago, the most important drawback of big data technologies was the lack of maturity. they have now evolved into more stable and robust architectures and have a lot more to offer. what is the state of the art? program salle a salle b salle a 09:00 - 09:25 welcoming and breakfast 09:25 - 09:30 opening 09:30 - 10:15 a crash course on google cloud automl and machine learning apis - google (en) kevin nelson developer advocate thanks to machine learning and ai, applications are now being created that can see, hear, and understand the world around them. learn how you can easily infuse ai into your business today. in addition to a guided walkthrough of easy-to-use machine learning apis from google cloud: cloud vision, cloud video intelligence, cloud speech, cloud natural language, and cloud translation, we'll demonstrate how google cloud automl enables developers with limited machine learning expertise to train high quality models by leveraging google’s state of the art transfer learning, and neural architecture search technology. 10:25 - 11:10 kafka beyond the brokers: stream processing and monitoring - confluent (fr) florent ramière technical account manager the kafka ecosystem goes way beyond the brokers: kafka connect, kafka stream and ksql are amazing tools! i propose to walk you through the implementation of all these components with a focus on streaming and monitoring. come join me to learn how to leverage kafka to put your data in motion! 11:10 - 11:35 break 11:35 - 12:20 how to deal with workflows lifecycle in apache nifi? - hortonworks (en) pierre villard solution architect apache nifi provides a revolutionary data flow management system with a broad range of integrations with existing data production, consumption, and analysis ecosystems, with robust data delivery and provenance infrastructure. this talk will mainly focus on how to deal with workflows lifecycle. 12:30 - 12:50 transforming pictures into memories - photobox (fr) adrien morvan & cristina oprean machine learning engineers photobox business is about pictures and derived products: we process 2 to 6 millions photos on a daily basis. to suggest adapted products to our customers we need to handle and better understand the content of their pictures. since the number of personal photos has greatly increased thanks to the development of digital cameras and smartphones, scalability is a must. the goal of this presentation is to introduce our large scale automatic photo labelling pipeline. 12:50 - 14:00 lunch break 14:00 - 14:45 exploring graphs: looking for communities & leaders - quantmetry (en) aurélia nègre & alberto guggiola data scientists ever been stuck in a data science use case where any approach seems too hard? graph theory, describing a system just in terms of nodes and links, could be your answer! in the practical example we’ll show, we’ll try to find data science communities and their leaders in linkedin. challenge accepted? 14:55 - 15:40 the internals of query execution in spark sql (en) jacek laskowski if you want to get even slightly better performance of your structured queries (regardless whether they are batch or streaming) you have to peek at the foundations of dataset api starting with queryexecution. that's where any query ends up at and my talk starts. the talk will show you what stages a structured query has to go through before execution in spark sql. i'll be talking about the different phases of query execution and the logical and physical optimizations. in the end, i'll do a live coding session to show the steps to write logical and physical optimizations in scala. 15:40 - 16:05 break 16:05 - 16:50 building a real time analytics api at scale - algolia (en) sylvain friquet software engineer this talk will cover how we redesigned our analytics api from the ground up to serve metrics in near real time from billions of events per day. we'll go through the tools we considered for the job to how we actually implemented our solution, starting from the datastore up to the whole data pipeline and its api, leveraging golang, kubernetes, gcp and citus. 17:00 - 17:20 real-time access log analysis - blablacar (en) thomas lamirault software architect at blablacar we have built a streaming platform to have fast insights about the usage of our services. i will show you how blablacar builds an automatic access log streaming analysis to improve the security and gain fine-grained knowledge of the platform usage. 17:30 - 18:00 keynote 18:00 - 19:15 cocktail salle b 09:00 - 09:25 welcoming and breakfast 09:25 - 09:30 opening 09:30 - 10:15 machine learning models at scale with amazon sagemaker - aws (fr) olivier bergeret solutions architect manager build, train, and deploy machine learning models at scale machine learning often feels a lot harder than it should be to most developers because the process to build and train models, and then deploy them into production is too complicated and too slow. amazon sagemaker includes modules that can be used together or independently to build, train, and deploy your machine learning models. 10:25 - 10:45 deep learning for vision into the wild - heuritech (en) charles ollion co-founder beyond the ai hype, significant new possibilities in the world of computer vision have arisen in the last few years. however, deploying computer vision solutions still requires expert vision knowledge, business understanding, solid engineering and smart processes. i’ll expose the challenges of computer vision applied to a vertical domain such as fashion, and how we solved them at heuritech. 10:50- 11:10 the wonders of deep learning: how to leverage it for natural language processing - tendam (en) ana peleteiro ramallo data science director in recent years, deep learning (dl) has proven to be a transformative force that has made impressive advances in different fields. in fact, within the area of natural language processing (nlp), deep learning has outperformed many former state of the art approaches, such as in machine translation or named entity recognition (ner). in this talk i will present various deep learning algorithms and architectures for nlp, with examples of how they can be leveraged to real world applications 11:10 - 11:35 break 11:35 - 12:20 tensors in the sky with cloudml - xebia (fr) sylvain lequeux data engineer out of curiosity, ask the other people in the conference room who h
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