18-02-2019 A sheet with final evalution can be found here.
11-01-2019 The deadline for the final report submission has been extended to January 21, 2019
11-01-2019 Presentations of the final reports will take place on:
- Wednesday, January 23, 15:10 (room L128 BT)
- Thursday, January 24, 13:30 (room L125 BT)
02-11-2018 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


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

The Challenge

The Data Ninja competition

For more information check:


Project's meetings

Schedule of the project's meetings

Information about project's meetings can be found here.


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
90% 5.0
80% 4.5
70% 4.0
60% 3.5
50% 3.0