Mašinsko učenje u praksi
Kurs za absolutne početnike
4 meseca, 2 puta nedeljno
Poglavlje 1 - Uvod u kurs

Upravo polećemo, upoznaćete Vladimira, instruktora kursa i on će vam pomoći oko bordinga...
1.1 Dobrodošlica VIDEO (1:10)

1.2 Kontekst kursa VIDEO (14:44)

1.3 Uvod u kurs VIDEO (20:18)

Poglavlje 2 - Uvod u Veštačku Inteligenciju

Osnovi veštačke inteligencije
In this section, we will learn why should we visualize data at all and we will see what are the characteristics of a good data visualization

Python i alati
It does not make sense to start drawing and doodling before thinking about the message we want to deliver. Let's ask ourselves a couple of questions and reflect on what and how shall we deliver our message to the target audience.
3.1 Uvod u Python VIDEO (45:39)

3.2 Anaconda okruženje VIDEO (45:26)

3.3 Visual Studio Code VIDEO (39:31)

Osnove Python jezika
Let's see what kind of graphs and charts can be used for specific visualization needs. We have to choose the right tool for a job.
4.1 Sintaksa i prosti data tipovi VIDEO (54:42)

4.2 Uslovi, petlje, nizovi i rečnici VIDEO (38:39)

4.3 Matplotlib VIDEO (39:09)

4.4 Plotly VIDEO (33:54)

4.5 Dash VIDEO (33:41)

4.6 Pred-procesiranje i analiza podataka VIDEO (33:41)

4.7 Python biblioteke VIDEO (14:33)

4.8 Python - fajlovi VIDEO (26:02)

4.9 Python konzerviranje podataka VIDEO (11:56)

4.10 Pandas biblioteka za analizu podataka VIDEO (1:27:46)

4.11 Pandas biblioteka - vežba VIDEO (1:14:31)

4.12 NumPy biblioteka VIDEO (1:14:31)

Week 2

Computer Vision
Graphs and charts are more verbose if decorated by doodles and they can tell entire stories if structured properly. Let's see some techniques and tips that can make our charts talk.
5.1 OpenCV VIDEO (1:04:55)

5.2 Barkod čitač VIDEO (13:28)

5.3 p

5.4 m

5.5 Quiz

End note
Thank you for participating in this course and I do hope that the knowledge and experience that you gained will help you to clearly express and communicate your data!

6.1 Course summary VIDEO (0:55)

6.2 What is next?