News

11-10-2016 The Data Ninja competition: the official launch of the competion (Friday, Oct. 13, 13.30, room 122 BT)
11-10-2016 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

11-10-2017 The mining massive data sets challenge [pdf]
13-10-2017 Launching of the "Data Ninja" competition (a talk by Tomasz Gramza from OLX) [pdf]
13-10-2017 Introduction to Artificial Intelligence by Amazon Web Services [pdf]
13-10-2017 Some words about the "Data Ninja" competition (a talk by Tomasz Gramza and Arkadiusz Robiński from OLX)
25-10-2017 Performance measures in the Data Ninja Challenge [pdf]
08-11-2017 Student's talk: Multi-label classification (Krzysztof Martyn)[pdf]
Student's talk: Word2Vec (Magdalena Dzięcielska)[pdf]
15-11-2017 Student's talk: Some simple approaches to face detection (Piotr Majorczyk)
Student's talk:
22-11-2017 Student's talk:
Student's talk:
29-11-2017 Student's talk: Deep reinforcement learning (Aleksandra Kobus and Maciej Uniejewski)
Student's talk:
06-12-2017 Presentation of students' reports
13-12-2017 Presentation of students' reports
20-12-2017 Student's talk:
Student's talk:
03-11-2018 Student's talk:
Student's talk:
17-01-2018 Presentation of students' reports
24-01-2018 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 here.

Evaluation

Lecture:
Report: data organization/processing: 45 points (min. 50%)
Report: predictive models : 45 points (min. 50%)
Students' talk : 10 points
Top score in the challenge : 10 points

Scale

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