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Conferences / PyCon (national Python conferences)

PyCon Lithuania 2019

May 24–26, 2019 · SMK University of Applied Social Sciences, Vilnius, Lithuania

Conference
PyCon (national Python conferences) Data science & ML
Dates
May 24, 2019 – May 26, 2019
Venue
SMK University of Applied Social Sciences
Place
Vilnius, Lithuania
Format
In person
Status
Past
Attendance
—
Website
pycon.lt
Recorded
20 sponsors · 42 speaker appearances
Notes
Tutorials Fri 24 May, conference Sat-Sun 25-26 May (pycon.lt history lists 25-26 May). Keynotes: Ian Ozsvald, Hynek Schlawack, Mike Müller. Speakers from the archived 2019 talks page (bios used for affiliations) plus the current pycon.lt 2019 talk list. Sponsor logos shown without tiers (a personal sponsor logo left out). Ticket prices not found (Paysera).

Ticket prices

No ticket prices recorded

Sponsors 20

Speakers and talks 42

SpeakerCompanyRoleTalkLinks
Hynek Schlawack—KeynoteMaintaining a Python Project When It's Not Your Job—
Ian OzsvaldMor ConsultingKeynoteCitizen Science with Python—
Mike MüllerPython AcademyKeynote——
Albertas GimbutasDanske BankTalkAuto Mock External Dependencies in Python Tests—
Andrius ŽilėnasINVENTSHIPTalkComputer Aided Innovation (CAI): what's state of the art now and expectations for the future—
Chetan KhatriAccion LabsTalkChallenges that everyone struggles while productionizing Apache Spark workloads—
Christopher Lozinski—WorkshopPyOdide/Iodide Tutorial—
Christopher Lozinski—WorkshopPug Training—
Dom WeldondecisionLabTalkInteractive Data Visualization Web Apps with no JavaScript: what you can, should and probably shouldn't do with plotly/Dash.—
Eivydas Vilčinskas—TalkSystem Administrators: to Python or not to Python—
Gediminas Žylius—TalkHow to use machine learning for better ranking results? The curious case of HomeToGo.—
Ian Davies—TalkAnvil: Full-stack Web Apps with Nothing but Python—
Ibukun Oluwayomi—TalkAspect Oriented Programming in Python—
Ibukun Oluwayomi—TalkContainer based architecture for Django applications—
Inga PopovaiteUniversity of IowaTalkUsing Python automated text processing to study group behavior in space analog facilities—
Jan PipekShowmaxTalkFun with histograms and the physt library—
John Bywater—TalkEvents, The Modern Object Orientation—
Joonatan SamuelVeriffTalkMachine learning project anatomy—
Jurgis Pralgauskis—TalkThe Power of Dict—
Justin Shenk—TalkPitfalls of emotion detection from video in production—
Justin Shenk—TalkVisualizing PyTorch and Keras layer saturation with delve—
Maciej MarekPhilip Morris InternationalTalkData Science at PMI - The Tools of The Trade—
Mantas Urbonas—TalkPorting Python to Lithuanian syntax in order to teach your 7-years-old kid to code—
Marcin SzymaniukTantusDataTalkPySpark - Data intensive processing in practice—
Martin ChristenFHNWTalkGeodata processing using Python and JupyterHub—
Matas ŠeimysOxipitTalkMoving a machine learning app from notebook to production—
Migle GabrielaiteUniversity of CopenhagenTalkCan python help save lifes?—
Mridul SethUCLouvainTalkNetwork Science, Game of Thrones and Airports—
Oleg ShydlouskiDoistTalkData pipelines. Slice and dice your data.—
Pēteris Caune—TalkBuilding an Open-source Django Side-project Into a Business—
Piotr Migdał—TalkVisualizing machine learning - from confusion matrices to a game—
Radovan KavickyGapData InstituteTalkData Science in Python: Past, Present and Future—
Sarah Diot Girard—TalkFrom ML experiments to production: versioning and reproducibility with MLV-tools—
Šarūnas NavickasTokenMillTalkPractical NLP—
Shaun Taylor-Morgan—TalkAnvil - Build a full-stack web app with nothing but Python—
Steph Samson—TalkPackage and Dependency Management with Poetry—
Stephanie Bracaloni—TalkHow to easily set up and version your Machine Learning pipelines, using DVC and MLV-tools—
Tomasz ChabinkaAlior BankTalkIntroduction to DevOps for Data Scientists and ML Engineers—
Tomasz ChabinkaAlior BankTalkEmbeddings: advanced dimension reduction technique in practice—
Valentas Gružauskas—TalkAgent-based Modelling and Reinforcement Learning for Route Scheduling: Integrating Open Source Software—
Vijayakumar Ravindran—TalkEnabling Autonomous Cloud Native infra as a code powered by Python—
Vladimir PuzakovRambler&CoTalkHow to deploy your python microservices with Kubernetes—

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