Uploaded April 2021 | Updated September 2026, 2 weeks ago
This Python tool working in Jupyter Notebook allows you to prepare a custom dataset for your learning purposes. This should be very useful when learning Machine Learning (ML) and Data Science algorithms.
This cool Python application is perfect to create your own dataset if you are get bored with some toys dataset such as Iris or Titanic. You can create your datasets for testing Machine Learning models not in minutes, but in seconds.
In this video I am demonstrating how to quickly generate dataset with a shape of scatter plot, line graph and histogram. To make it more fun, some datasets I will save to CSV files while other one (for line graph) to JSON file. Just draw lines, curves and bins by mouse and data will be generated automatically based on your graph.
This approach allows you to test Machine Learning algorithms and models with very different datasets and its combinations.
If you want to take a deeper look into this cool Python package, check the references below:
Drawdata Pip installation: pypi.org/project/drawdata
Official drawdata package Github repository: github.com/koaning/drawdata
The content of the video:
0:00 - Quick intro into drawdata package
0:45 - Run drawdata package in Jupyter Notebook
7:15 - Announcement about the next video for MLOps
I hope you enjoyed this video. If you want to get more useful content for Data Science, Machine Learning, MLOps, Python programming, and more - subscribe my channel! Link is here: youtube.com/c/VytautasBielinskas
See you there!
#machinelearning #datasets #datascience
This Python tool working in Jupyter Notebook allows you to prepare a custom dataset for your learning purposes. This should be very useful when learning Machine Learning (ML) and Data Science algorithms.
This cool Python application is perfect to create your own dataset if you are get bored with some toys dataset such as Iris or Titanic. You can create your datasets for testing Machine Learning models not in minutes, but in seconds.
In this video I am demonstrating how to quickly generate dataset with a shape of scatter plot, line graph and histogram. To make it more fun, some datasets I will save to CSV files while other one (for line graph) to JSON file. Just draw lines, curves and bins by mouse and data will be generated automatically based on your graph.
This approach allows you to test Machine Learning algorithms and models with very different datasets and its combinations.
If you want to take a deeper look into this cool Python package, check the references below:
Drawdata Pip installation: pypi.org/project/drawdata
Official drawdata package Github repository: github.com/koaning/drawdata
The content of the video:
0:00 - Quick intro into drawdata package
0:45 - Run drawdata package in Jupyter Notebook
7:15 - Announcement about the next video for MLOps
I hope you enjoyed this video. If you want to get more useful content for Data Science, Machine Learning, MLOps, Python programming, and more - subscribe my channel! Link is here: youtube.com/c/VytautasBielinskas
See you there!
#machinelearning #datasets #datascience
![XAMPP ir Wordpress instaliacija + paruosimas darbui [LT]](https://i.ytimg.com/vi/hauMwxewpmo/mqdefault.jpg "XAMPP ir Wordpress instaliacija + paruosimas darbui [LT]
Šiame video pristatau, kaip reiktų paruošti vieną populiariausių virtualių serverių XAMPP darbui. Taip pat, kaip į XAMPP aplinką instaliuoti ir paruošti pilnaverčiui darbui WordPress turinio valdymo sistemą internetinėms svetainėms kurti.
Šiame video pamatysite:
1. XAMPP atsisiuntimas ir instaliacija: 0:07
2. Sisteminiai virtualaus serverio pakeitimai: 1:14
3. WordPress atsisiuntimas ir instaliavimas: 2:40
4. Virtualios duomenų bazės sukūrimas: 3:56
5. Wordpress paruošimas darbui: 5:31
**Naudotos atsisiuntimo nuorodos**
- XAMPP: https://www.apachefriends.org/index.html
- Wordpress https://wordpress.org/
Norite daugiau pamokų? Kreipkitės vytautas.bielinskas@gmail.com")
