News

02-11-2019 The revised schedule of the students' talks can be found below in Section "Schedule of lectures"
30-10-2018 The Data Ninja competition: the official launch of the competition (Wednedsay, Nov. 7, 15.10, room L128 BT)
30-10-2018 The competition web page has been launched.
17-10-2018 Office hours cancelled on Thursday, October 18, because of the PP-RAI conference (please email me with you want to meet).
10-10-2018 The challenge has begun :)

The aim and the scope of the challenge

The aim of the course: To learn how to deal with real-life massive data (or to win a data mining competition).

The scope of the course: Application of data mining algorithms to real-life massive data:


Main information about the course

Time and place


Lectures

Schedule of lectures

11-10-2018 The mining massive data sets challenge [pdf]
07-11-2018 Launching of the "Data Ninja" competition
14-11-2018 Students' talk: Natural language processing (Zofia Długosz, Michał Rajewski)
Students' talk: Deep networks: TensorFlow (Jakub Białek, Patryk Kuśmierkiewicz)
Student's talk: Building Autoencoders with Keras Library (Adam Ćwian, Filip Grześkowiak)
21-11-2018 Students' talk: Deep networks: Torch (Jan Andraszyk, Łukasz Jędryczka)
Students' talk: Deep Networks: Theano (Jan Cofta, Konrad Śniatała)
Students' talk: Multi-label classification (Patryk Smól, Wojciech Bełka)
12-12-2018 Students' talk: Deep reinforcement learning (Jan Klimaszyk, Marcin Sendecki)
Students' talk: Positive-unlabelled learning (Łukasz Osiński, Mateusz Lewandowski)
Students' talk: Active learning (Damian Szalbierz, Kamil Szmajdziński)
19-12-2018 Students' talk: OpenAi Gym (Paweł Szudrowicz, Dominik Białecki)
Students' talk: Microsoft Azure for Big Data and Machine Learning (Grzegorz Kotlarz, Radosław Waberski)
Students' talk: Zero-shot learning (Dawid Ciok, Adam Kokosza)
09-01-2019 Students' talk: ML Packages: MLib (Amadeusz Mileszko, Filip Philavong)
Students' talk: TBA (Wojciech Dizałowski, Jakub Drapiewski)
16-01-2019 Presentation of students' reports

The Challenge

The Data Ninja competition

For more information check: dataninja.olx.pl


Reports


Project's meetings

Schedule of the project's meetings

The schedule of the project's meetings can be found .. [TBA]


Evaluation

Lecture:
Report: your approach to win the competition: 70 % of points (min. 50%)
Seminar students' talk : 30 % of points
Top score in the challenge : Bonus of 10 percent points
Scale:
90% 5.0
80% 4.5
70% 4.0
60% 3.5
50% 3.0