PyData Warsaw #6: Deep & Machine Learning + After Party

About

This will be the sixth PyData Warsaw regular meetup at Centrum Szkoleniowe Adgar Ochota near Warszawa Zachodnia station (English: Warsaw West).

Location: http://en.adgarochota.pl/contact/location

room number: "Event Room"   

Doors open at 18:30, talks start at 19:00pm, about 9pm we move to a pub. We are ready to host 150 folk in the room so there may be plenty of people to discuss data science questions with!

Please remember to unRSVP if you realize you can't make it - it will help a lot for our crew.

And make sure you follow @pydatawarsaw for any updates and early announcements.


First Talk - Mateusz Opala & Michał Jamroż:

"Deep learning for image segmentation"

Deep learning techniques ignited a great progress in many computer vision tasks like image classification, object detection, and segmentation. Almost every month a new method is published that achieves state-of-the-art result on some common benchmark dataset. In addition to that, DL is being applied to new problems in CV.

In the talk we’re going to focus on DL application to image segmentation task. We want to show the practical importance of this task for the fashion industry by presenting our case study with results achieved with various attempts and methods.


Second talk - Monika Kuryś 

"#startedfromthebottom"
"This is a short story. I will tell u about how an accountant can get from the world of boring numbers to typical "into programming" world. I will tell You how can you get started your Machine Learning story. Basics, so How to eat an egg with a fork? How to get Your s*it together, when You land in the middle of the "nerdland"."


Third talk - Yaz Santissi


"Image Recognition with TensorFlow using Python "
Images form a significant part of data.  Yet, until recently, it was difficult to programmatically extract metadata about images.  Now, thanks to TensorFlow, we are able to develop algorithms that can give us information about images.  In this presentation, Yaz will show us how to quickly get set up with TensorFlow using containers.  To be even more efficient, what is becoming known as transfer learning will be demonstrated.  An existing image recognition model will be used rather than the time-consuming approach of building one from scratch.  Subsequently, this classifier model will be trained with new images.  And finally, there will be a live test of this model applied to random new images.


Agenda:

18:00 - 18:30 - Doors open

19:00 - 19:05 - Introduction

19:05 - 19:45 - First Talk 

19:45 - 20:25 - Second Talk 

20.25 - 21:05 - Third Talk

21:05 - 21:10 - "Speed Dating"

21:10 - 24:00 - After Party with our Partner, drinks for free !!! (at Świeżo Malowane)


PS1: default language is English, but there may be some exceptions from the rule

PS2: presentation part is mainly Python focused but not only, We expect to host a number of guests working with R, Scala and other languages. 

direct contact: [masked]

See you !

Event Organizers
  • Medium eventil