dmitrymakarov.ru
RegisteredDmitry Makarov - a portal for those who want to understand machine learning without unnecessary noiseDmitrymakarov website. ru is like a quiet library on the Internet, where everyone can f...
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Website Description
Dmitry Makarov - a portal for those who want to understand machine learning without unnecessary noise
Dmitrymakarov website. ru is like a quiet library on the Internet, where everyone can find material that really helps. Don't rush past it, even if you're just starting your journey in the world of analytics or mathematics. There is no clickbait, no advertising on every page, just pure knowledge. The site is dedicated precisely to talking about machine learning and mathematics - but in a way that is understandable, even if you have not encountered it before.
All materials here are collected around several key topics. There is an introductory course on machine learning - it is suitable for both beginners and those who want to brush up on the basics. Programming in Python is also available, and without unnecessary hassles, which is very valuable. And also - data analysis, information processing, model training. It’s as if someone took a complex topic and sorted it out, slowly, with love for detail.
Mathematics: the foundation that many people hide
The section on mathematics seems especially interesting. There are not just formulas, but explanations. Bayesian statistics is not just an abstraction, but something that is actually used in real-world problems. Information Theory - Part 1 and Part 2 - covers how data communication works, how we can measure information. Sometimes it seems that everything is too complicated, but the author knows how to simplify without losing the essence. And yes, sometimes you feel that the text is written from the heart, and not according to a template.
- What is the Bayesian approach?
- Why is information theory important for training models?
- How does Python help in data analysis?
References are not just a formality. Classic books listed here: Bishop, Hastie, Murphy, Mohri, Zaki. All of them are the gold standard in their field. You can, of course, read them yourself, but here are tips on how to start and where to focus. It's as if an experienced teacher gave you a list so as not to waste time on unnecessary things.
Real site, real author
The interface is simple, but not primitive. No complicated menus, no annoying animations. Everything is built around content. The page is called Dmitry Makarov - and this is not just a name. The author wants to be recognized, not through advertising, but through the quality of materials. He does not shout about himself, he simply does what he considers necessary - shares his knowledge.
The year of the last update is indicated as 2025. It may seem strange, but Internet sites rarely change the year if everything works. And here you can see that the project is alive and relevant. Not a hosting stub, not a temporary page. This is not a sales platform, not a blog with paid articles. Just a person who loves his topic and wants to help others.
Frequently asked questions about the dmitrymakarov website.ru
What is this site about?
The site is dedicated to machine learning and mathematics. Here you can find introductory courses, materials on data analysis, Python programming, Bayesian statistics and information theory. All materials are collected for those who want to learn on their own.
Who is the author of the site?
The author is Dmitry Makarov. He wrote all the materials, compiled the bibliography, and created a portal to help people understand complex topics without fluff.
Can these materials be used for free?
Yes, the materials are available for free. The site does not contain advertising or paid sections. All that is presented is open knowledge that is shared without restrictions.
What books are recommended in the bibliography?
The list includes classic textbooks: Bishop C. M., Pattern Recognition and Machine Learning; Hastie T., Tibshirani R., Friedman J., The Elements of Statistical Learning; Murphy K. P., Machine Learning: a Probabilistic Perspective; Mohri M., Rostamizadeh A., Talwalkar A., Foundations of Machine Learning; Zaki M. J., Meira W., Data Mining and Machine Learning.
Why does the site look so simple?
Simple design is part of the site’s philosophy. The author decided not to overload the page with elements, but to focus on the content. The goal is to help the reader focus on learning rather than design.
Sometimes it seems that everything is too perfect. But no - there are small errors, missing commas, repetitions of thoughts, sometimes even strange wording. And that's okay. This is a person, not a machine. That's the whole secret of success. He doesn't run for attention, he just does his job. Isn't that enough?
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domain: DMITRYMAKAROV.RU
nserver: ns1.spaceweb.ru.
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state: REGISTERED, DELEGATED, VERIFIED
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created: 2009-02-23T21:00:00Z
paid-till: 2027-02-23T21:00:00Z
free-date: 2027-03-27
source: TCI
Last updated on 2026-06-09T23:43:01Z
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