The Virtual Machine Learning Laboratory with Visualization of Algorithms Execution Process

  • Vadim D. Kholoshnia
  • Elena A. BoldyrevaEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 188)


This paper describes the development of a virtual laboratory for teaching various machine learning algorithms with a visualization of the execution process. The novelty of the results lies in the fact that, in contrast to existing virtual machine learning laboratories, the presented one provides the visualization system for machine learning algorithms execution process which instantly shows changes by the parameters and changes in the software implementation code. Also, the open-source structure of an algorithm provides an ability for third-party interested developers to add their own lessons that have passed the validation. Visualization of the machine learning algorithms execution process is demonstrated by the example of solving the task of finding the shortest path. The student can independently build a map of the area in 2D and 3D, dynamically change it and trying different algorithms to find the shortest path. This allows for a comparative analysis of various machine learning algorithms when it comes to spatial orientation. The developed laboratory currently has no analogues among widely available software tools for training specialists in the field of data science and machine learning.


Virtual laboratory Machine learning Shortest path finding 2D visualization 3D visualization Visualization of execution process 


  1. 1.
    Pramono, S.E., Prajanti, S.D.W., Wibawanto, W.: Virtual laboratory for elementary students. J. Phys. Conf. Ser. 1387, 012113 (2019).
  2. 2.
    Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Guetl, C., Petrović, V.M., Jovanović, K.: Virtual laboratories for education in science, technology, and engineering: a review. Comput. Educ. 95, 309–327 (2016). ISSN 0360-1315.
  3. 3.
    Son, J., Irrechukwu, C., Fitzgibbons, P.: Virtual lab for online cyber security education. Commun. IIMA 12 (2012)Google Scholar
  4. 4.
    Rajendran, L., Veilumuthu, R.: A study on the effectiveness of virtual lab in E-learning. Int. J. Comput. Sci. Eng. 2 (2010)Google Scholar
  5. 5.
    Hwang, W.-Y., Kongcharoen, C., Ghinea, G.: To enhance collaborative learning and practice network knowledge with a virtualization laboratory and online synchronous discussion. Int. Rev. Res. Open Distrib. Learn. 15(4) (2014).
  6. 6.
    Yosinski, J., Clune, J., Nguyen, A.M., Fuchs, T.J., Lipson, H.: Understanding Neural Networks Through Deep Visualization (2015).
  7. 7.
    Vega, O., Londoño-Hincapié, S., Toro-Villa, S. Virtual Labs for Science Teaching. Ventana Informatica (2016)Google Scholar
  8. 8.
    Russell, I., Markov, Z., Neller, T.: Teaching AI through machine learning projects. In: Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITICSE ’06). Association for Computing Machinery, New York, NY, USA, p. 323 (2006).
  9. 9.
    Indian Institute of Technology Bombay, Machine Learning Lab: Last accessed: 9 Mar 2020
  10. 10.
    Google: AI experiments. Last accessed: 9 Mar 2020
  11. 11.
    Microsoft, AI Lab, Last accessed: 9 Mar 2020
  12. 12.
    Cloud Academy, TensorFlow Machine Learning on the Amazon Deep Learning AMI, Last accessed: 9 Mar 2020
  13. 13.
    Baker, B., Kanitscheider, I., Markov, T., Wu, Y., Powell, G., McGrew, B., Mordatch, I.: Emergent tool use from multi-agent autocurricula (2019). ArXiv, abs/1909.07528Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.ITMO UniversitySaint PetersburgRussia

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