Removing my old website by Google.

My old website with 151 notes was deleted on 10 Mar. 2023, 08:58 by a “Google” user.

Between 2011 and 2020 I used another home page which was Unfortunately, my old website was deleted on 10 Mar. 2023, 08:58 by a “Google” user. And I have no means to recover it.

During my career and educational paths, I as a fox peeked my nose into different fields relative to Computer Science (CS) because I found it fun and entertaining. My old webpage contained 151 personal notes and did not contain any advertisements.

During 2015 and up to 2023 my old homepage has been visited by 34’755 users. Total users have made 87’329 views of this content. The users of my old website were from 144 countries around the globe. Therefore, the content was not only useful for me, but also for another 34’755 users. The top 20 countries (from a total amount of 144) of unique visitors to the old home page are presented in the table below.

Unique Visitors Country
13 394 Russia
5 263 USA
2 896 Ukraine
1 099 India
1 074 Belarus
955 Germany
812 UK
486 China
436 Canada
436 France
347 Japan
436 Poland
292 Kazahstan
285 Netherlands
249 Italy
241 Spain
240 Saudi Arabia
226 Sweden

Future of Old Notes

I have some backups for the notes. And I would be glad to structure my notes well, but it’s a time demanding procedure. For this, I need a lot of free time, which I don’t have.

Google has created a means to transition from the old website to the new one, but in my case, it did not work flawlessly.

Examples of Topics of Old Public Personal Notes

  • Notes about the book of A.N.Kolomogorov, S.V.Fomin - Introductionary Real Analysis.
  • Notes about the book of Amir Beck, First-Order Methods in optimization, 2017. That note has been shared with prof. Amir Beck.
  • Notes about EE263, EE364A, and EE364B courses at Stanford Jr. University from prof. Stephen P. Boyd.
  • Overview of some papers in Deep Learning for Image tasks.
  • Physics questions are important for physics-based simulation and Robotics.
  • My reflections on various problems of Machine Learning.
  • My reflections on how AI and Machine Learning should be systematized.
  • Usage of programming languages Python, Matlab, C++, Perl, R, JAVA, and software development frameworks such as Qt.
  • Using specialized software development frameworks: Google TensorFlow, PyTorch.
  • GPU programming (CUDA, OpenCL, OpenGL).
  • Developing at a user-space level for Linux/Posix OS and Windows Family OS.
  • Convex Optimization and Numerical Optimization.
  • Notes about various mathematical tools, including Fourier Transform and Fourier Series.
  • Classical things from Linear Dynamical Systems and classical (at least for people aware of Convex Optimization) things in Control.
  • Thinking about concepts from Statistics and Machine Learning: KL-divergence, Gini index, Math behind backpropagation.
  • Describing popular tricks for Deep Learning.
  • Understanding Decision Trees from scratch.
  • Considering all stages of applying Machine Learning in the industry.
  • Different ways try to systematize AI and ML approaches their possibilities.
  • Complete derivations and problem formulations of SVM, Logistics Regression.
  • Jargon applied in Classification problems and in Machine Learning.
  • Usage aspects of Z3 solver from Microsoft Research.

Written on March 13, 2023