Digital analytics meetup #13 – Kaggle & Google Analytics

Ήρθε το πρώτο Digital Analytics Meetup για το 2019! Για άλλη μια φορά θα έχουμε μια συνάντηση φτιαγμένη για όσους δουλεύουν ή ενδιαφέρονται να απασχοληθούν ως data scientists. Βασικό θέμα συζήτησης θα είναι το Kaggle & Google analytics (https://analytics.google.com/analytics/web/). Επίσης θα δούμε τον διαγωνισμό που τρέχει αυτή τη στιγμή στο Kaggle(https://www.kaggle.com/c/ga-customer-revenue-prediction) και έχει ως στόχο να προσπαθήσουν οι συμμετέχοντες να προβλέψουν το χρηματικό ποσό που θα ξοδέψει ο κάθε επισκέπτης ενός website.

Παρουσιάσεις
Για όσους δεν έχουν έρθει σε προηγούμενα meetup ή έχουν ελάχιστη εμπειρία στα web analytics και το Kaggle θα κάνουμε στην αρχή της συνάντησης μια εισαγωγή και στα δύο. Η Χριστίνα Τσιριπίδου (https://www.linkedin.com/in/christinatsiripidou) θα μας ξεναγήσει στον τρόπο λειτουργίας του Google analytics και θα μας δείξει τι είδους δεδομένα υπάρχουν διαθέσιμα για ανάλυση. Για όποιον έχει ενδιαφέρον για αυτό το θέμα μπορεί να δει περισσότερα για τα web analytics από το 2ο meetup. 

Ο πρώτος διαγωνισμός machine learning της Kaggle με δεδομένα βασισμένα στο Google Analytics είναι γεγονός. Με αφορμή αυτό ο Αλέξανδρος Παπαγεωργίου (https://www.linkedin.com/in/alexandrospapageorgiou/) θα μιλήσει σχετικά με τα πολλαπλά οφέλη που μπορεί να προσκομίσει κάποιος μέσω Kaggle, παραθέτοντας πολλά και διάφορα παραδείγματα μέσα από τη δική του πρόσφατη εμπειρία και με την συμμετοχή του στον διαγωνισμό. Ο διαγωνισμός καλεί τους συμμετέχοντες να αναλύσουν το αρχείο online επισκέψεων στο Google Merchandise Store (γνωστό και ως GStore) για να προβλέψουν το κέρδος ανά πελάτη. Το αποτέλεσμα μπορεί να βοηθήσει επιχειρήσεις με online παρουσία να προσεγγίσουν πιθανούς πελάτες με διαφορετικούς τρόπους ή να βελτιστοποιήσουν τον τρόπο που κατανέμουν τον προϋπολογισμό του marketing.

Ο Αλέξανδρος είναι independent consultant στην αναλυτική δεδομένων με εξειδίκευση στο digital analytics. Εργάστηκε ως marketing account manager στο Δουβλίνο της Ιρλανδίας με την Ελληνική ομάδα της Google και στη συνέχεια ως consumer behaviour analyst στη μηχανή αναζήτησης υπηρεσιών υγείας Whatclinic.com. Είναι απόφοιτος του τμήματος data analytics του National College of Ireland και κατέχει μεταπτυχιακό στα πληροφοριακά συστήματα απο το TUCS Finland.

Πρόγραμμα
Με αυτή την συνάντηση επιστρέφουμε στο γνωστό πρόγραμμα και των προηγούμενων συναντήσεων μας:
18.30 Μαζευόμαστε στο φουαγιέ του OK!Thess, για να γνωριστούμε και να τσιμπήσουμε snacks
19.00 Ξεκινάνε οι παρουσιάσεις
20:30 Ολοκλήρωση των παρουσιάσεων. Όπως πάντα θα έχουμε χρόνο να γνωριστούμε καλύτερα, να πιούμε μπύρες παρέα και να συζητήσουμε θέματα που απασχολούν την κοινότητα και προτάσεις για επόμενα meetup

O χώρος του meetup είναι στο φουαγιέ του ισογείου του OK!Thess, γωνία Κυδωνιών & Μαρίας Κάλλας, στην περιοχή του Μεγάρου Μουσικής.

Περισσότερες λεπτομέρειες για αυτή την συνάντηση, προηγούμενες συναντήσεις και νέα της κοινότητας μπορείτε να δείτε στην σελίδα του meetup:
https://digitalanalytics.gr/interesting-news/digital-analytics-meetup-13-kaggle-google-analytics-okthess-28-%CE%B9%CE%B1%CE%BD-2019/

5 years Thessaloniki Java Meetup celebration

We are absolutely delighted to announce this meetup to celebrate our 5th anniversary! Join us at i4G Pro with two special guests.

Vaggelis Spathas (https://www.linkedin.com/in/vaggelis-spathas-2380ab29/), a Software engineer working on java programming at BETA CAE, will discuss “How to analyze your JVM application’s performance. Tools and techniques” and Ioannis Kolaxis (https://www.linkedin.com/in/ioannis-kolaxis/), Software Engineer @ Atos will explain how to “Improve the quality of your software in 6 steps”

Here is a non-restrictive schedule of the meetup event
19:00 – 19:10 – Networking / Socializing
19:10 – 19:55 – How to analyze your JVM application’s performance. Tools and techniques
19:55 – 20:00 -Short break
20:00 – 20:45 – Improve the quality of your software in 6 steps”
20:45 – 21:30 – Vassilopita, beers, giveaways, presents, socializing, networking

Below you can find the talk abstracts

1. How to analyze your JVM application’s performance. Tools and techniques
Where my app consumes all the time? How much it costs in CPU time a current method execution in your production environment? Can there be any memory leak in your app? What is happening with garbage collection and allocation rates? Is there any deadlock?
This talk will focus on techniques and tools for gathering metrics from JVM applications. Using tools like JVisualvm(https://visualvm.github.io/) and Arthas(https://github.com/alibaba/arthas) to measure, analyze and improve our application’s performance.

2. Improve the quality of your software in 6 steps
Do your customers keep complaining about bugs in your software application? Does it take you too much time to implement new features?
If you answered yes, then you probably have issues with the quality of your software application. Here are 6 practical steps that you could follow, to improve its quality.

25th Blockchain meetup: The EOS Platform

In this meetup the ComeTogether team (https://cometogether.network/) is going to introduce EOS to us.

The agenda for the meetup is:

19.00 – 20.00 Introduction to EOS
20.00 – 20.15 Break
20.15 – 21.15 Example EOS Application
21.15 – 21.30 Discussion / networking / end

Abstracts:

Introduction to EOS
The audience is going to be introduced to the basic concepts and characteristics of the EOS platform. It will go through how scalable EOS is (explaining the consensus algorithm), as well as it’s governance and token model.

Example EOS Application
The ComeTogether EOS protocol/app is going to be discussed. From design decisions to implementation the audience will get an idea of how to go through the process of implementing an app in EOS. A demonstration of the app is going to conclude the talk.

Short Biographies of presenters:

Lazaros Penteridis (Founder/CEO)
Former AI and Robotics software engineer for 3 years. Has developed cloud robotics solutions, for clients such as Ericsson. MSc in Electrical and Computer Engineering from Aristotle University of Thessaloniki (AUTH).

Stavros Antoniadis (Co-Founder/Blockchain engineer)
Deep into smart contract development and cryptoeconomics. Formerly, mobile developer and test automation engineer at Schoox Inc. Final year student in Electrical and Computer Engineering, AUTH.

Nikos Chatzivasileiadis (Co-Founder/Full stack engineer)
Wide spectrum of software skills. Formerly, web developer intern at Veltio Greece Ltd. Final year student in Electrical and Computer Engineering, AUTH.

Stathis Mitskas (Co-Founder/Full stack engineer)
Has acquired three master degrees (CS, Finance-Banking, Leadership), two of which at the University of Bristol. Has been awarded the best paper on the 1st Workshop on Blockchain-enabled Networked Sensor Systems (BlockSys 2018).

The environment is casual and there will be plenty of opportunities to learn and more importantly get to know each other. After the event everyone is welcome to one of the nearby cafeterias to get to know each other.

Hope to see you there!

Συνάντηση 2019.01

Γεια χαρά σε όλους και καλή Χρονιά!

Την Πέμπτη 31 Iανουαρίου στις 19.00 θα τρέξουμε το επόμενο Athens Python Meetup, στα γραφεία της yodeck (https://www.yodeck.com/) στην Ομόνοια (1ος όροφος), που προσφέρθηκαν να μας φιλοξενήσουν και τους ευχαριστούμε για αυτό.

Θα μας μιλήσει ο Παντελης Πετρίδης [0], Co-Founder της Elorus (https://www.elorus.com/), σχετικά με “Horizontal scaling using Sharding in Django”.

Όπως πάντα μετά το τέλος της ομιλίας θα υπάρχει χρόνος για να τα πούμε, να γνώριστούμε και να ανταλλάξουμε απόψεις πάνω στην Python 🙂

Τα λέμε εκεί!

[0] Παντελης Πετρίδης: https://www.linkedin.com/in/pantelis-petridis-27b817/)

Let’s talk about … Java Security, Testing practices and Team dynamics

Happy 2019 to everybody!

We set the bar high with our last talk of 2018, so we needed an equally challenging event for 2019.

So, we are welcoming 2019 with a mini-conference and presenters from three different countries and two different continents:-)

This time we will host three different talks

1. A talk on Java security architecture, by Martin Toshev, of the Bulgarian Java User Group and Software Architect at Resolve Systems

2. Agile Testing Practices, with examples on Java, by John Pourdanis, Test Automation Engineer, ISTQB Certified Tester working for Pheron LTD (of the SchooX group)

3. How (not) to produce Software, and the intricacies of the team by Dimos Madarakis, Software Engineer @Tokyo, Japan (tele-conferencing)

More details on each talk, will be added in the following week, but I hope you are intrigued enough to rush and secure a place in the meetup:-)

We will be especially happy to have participants from other meetups, or any working software engineers that would like to expand their horizons:-)

Cryptocurrency Social meeting (last of 2018)

Κοινωνική συνάντηση στο crypto-friendly μαγαζί “Dastart” (http://www.dastart.com — στον πάνω όροφο) για να “τα πούμε” μια τελευταία φορά πριν το νέο έτος !

Social meetup at “Dastart” (http://www.dastart.com — upstairs) to get to hang out one last time before the New Year!

Hope to see you there!

And Merry Christmas to everyone !!

Networking & Xmas drinks – Digital Analytics Meetup #12

Καθώς μπαίνουμε στις γιορτές είπαμε να κάνουμε μια συνάντηση διαφορετική από τις προηγούμενες! Πέμπτη, 20 Δεκεμβρίου βρισκόμαστε στο bar Έπαυλη Μαρόκκου (Βασ. Όλγας 133, πρώην αστυνομία). Θα είμαστε εκεί από τις 20:00 για να γνωριστούμε καλύτερα και να πιούμε ένα (ή και παραπάνω) ποτά όλοι μαζί.
Ελάτε να ανταλλάξουμε ιδέες για επόμενα meetup, να συζητήσουμε αυτά που σας άρεσαν ή σας απογοήτευσαν μέσα στην χρονιά αλλά και για να μάθουμε λίγο καλύτερα ο ένας τον άλλο.
Σε αυτή τη συνάντηση δεν θα υπάρχουν ομιλίες.

Reinforcement Learning: All you need to know

Join us to learn all you need to know about Reinforcement Learning: a thorough introduction, examples, coding, and Deep Reinforcement Learning!

Agenda:
19:15: ‘Reinforcement Learning: An Introduction’, Anestis Fachantidis
20:15: ‘Practical Deep Reinforcement Learning’, Nikolaos Passalis
21:00: Networking and socializing

‘Reinforcement Learning: An Introduction’, Anestis Fachantidis

Abstract: Reinforcement Learning (RL) is one of the most ambitious fields of Machine Learning (ML) today. It has attracted a lot of publicity in the last decade, especially after its recent successes such as that of AlphaGo defeating Lee Sedol in the game of Go. Apart from games, what are the other applications of RL ? How does it work and what differentiates it from the rest of the ML approaches ? From designing reward and state signals to the exploration/exploitation problem and the basic RL algorithms we will try to gain an intuitive understanding of the fundamental aspects of RL and we will also take a quick look on how we can represent and solve an RL problem.

Bio: Anestis Fachantidis is Lead Data Scientist in the Intelligent Systems Lab at the Department of Informatics, Aristotle University of Thessaloniki (AUTH) and a Machine Learning postdoctoral researcher at the same department. He has been an Adjunct Faculty member at the Department of Informatics, AUTH, teaching Business Intelligence, Operational Research and Machine Learning (2016-2018). He holds a PhD in Machine Learning from the Department of Informatics, AUTH, a MSc degree in Information Systems from the Department of Applied Informatics, University of Macedonia, and a Bachelor Degree in Mathematics from the Aristotle University of Thessaloniki. As a Data Scientist, he has designed and developed ML systems for major Greek Businesses including systems for demand forecasting, customer segmentation and fraud detection. As a researcher, his interests focus on Reinforcement Learning, Transfer Learning and Business Intelligence. He has published several articles in refereed journals and conference proceedings and served as a Program Committee member to some of the most significant AI and Machine Learning conferences. He has been a visiting researcher in the Center For Robotics and Neural Systems (CRNS), Plymouth, U.K (2012) and is a member of the Association for Computing Machinery (ACM) and the IEEE Computational Intelligence society since 2013.

‘Practical Deep Reinforcement Learning’, Nikolaos Passalis

Abstract: Combining Deep Learning models with Reinforcement Learning (RL) techniques led to the development of powerful algorithms for solving various problems, ranging from playing Atari to developing self-driving cars, often outperforming humans! However, the large number of different Deep RL methods that have been recently proposed, together the vast amount of different hyper-parameters that must be tuned, leads to a large number of design choices that must be taken before even attempting to train a Deep RL agent. Therefore, it is not always straightforward to directly use Deep RL to tackle the problem at hand and a significant amount of experimentation and fine-tuning might be required. In this hands-on tutorial we will go through the most important deep RL algorithms and we will implement them from scratch using PyTorch! We will examine various ways to debug the algorithms, solve various issues that might arise and apply them in different problems.

Bio: Nikolaos Passalis obtained his Ph.D. in Informatics, specializing in Deep Learning, from the Department of Informatics, AUTh in 2018. Starting from December 2018, he will be postdoctoral researcher at the Signal Processing Laboratory of the Technical University of Tampere, Finland. He has (co-)authored more than 30 papers published in international journals and conference proceedings. His research interests include deep learning, computational intelligence and information retrieval.