DEV Community: Alex Maszański

What have I been doing last month?

Alex Maszański — Wed, 23 Dec 2020 09:53:38 +0000

Hello for everyone!
In my last article I wrote about my plans for the past month. And now I'm really happy with the progress I've made over the last 5 weeks!

So, what have I been doing last month?
• I finished a couple of Kaggle micro-courses: Python and Pandas as I planned a month ago. In these courses I learned basic Python concepts that will help me start learning data science. Two certificates and two pieces of very useful knowledges in my pocket!

• Further, I repeated Linear Algebra by this course. It's paid but here is a YouTube playlist. And by the Russian source mathprofi I learned derivative, integrals, derivative, series in mathematics and limits.

• Another math related thing is NumPy – Python library which is most widely used for carrying out mathematical operations that involve matrices. The most important feature of NumPy that sets it apart from other libraries is its ability to perform lightning speed calculations. I read this article, but, unfortunately it wasn't enough for me... Do you have other NumPy resources? Apart from the official documentation, of course :)

• Next, I realized that just theory in a library as Pandas and NumPy is not enough! My solution is a lot of practice.

For the NumPy I do this and this. I find these exercises a little bit hard, but worth it.

On the other hand, for Pandas I found more outstanding things:
Exercises and passing these exercises on YouTube. Learning by Doing!
And here is my repository :)

• Also I read a Russian-language book about statistics: Stats in Cats. And now I'm taking a statistics course. It is in Russian too, but it seems wonderful to me. Here.
But I have a lot of interesting material about statistics in English! So, maybe I'll write a separate article about it :)

And now I want to tell about my plan on tomorrow challenge #66daysofdata:
• End my statistics course (now I'm in the 2nd week)
• I need Data Visualization Kaggle micro-course. Because 7th pull of the Pandas exercises is about visualization, and I know nothing about Seaborn and Matplotlib! :(
• Practice and more practice! I have to finish Pandas and NumPy exercises. For instance, now my NumPy repo looks extremely sad...
• Before starting a full-fledged Data Science/Machine Learning course (By the way, I think between Andrew Ng and MIPT/Yandex) I need to know something about Theory of Probability.
• Maybe start this book?
• And I also want to write articles about learning Pandas and statistics. The best way to consolidate your knowledge is to put it on paper or in a blog.

From tomorrow I will regularly tweet my daily plan.

Thanks for the attention! Any suggestions to this article is always welcome. Please don’t forget to comment on this article if you found any mistakes :D

#66daysofdata and the workload

Alex Maszański — Fri, 20 Nov 2020 19:44:04 +0000

For a long time one idea won’t leave me alone – the flashmob #66daysofdata on Twitter!

Unfortunately, now I am under pressure in my university :c But I’m eager to try it
Well, vacation at my university will be about two months – January & February. But there are only 59 days at these months! So, it means that in December I need to spend another 10 days on this challenge. According to my calculations, I’ll be able to do this from the 23rd of December (By the way, we’re take into account the Christmas holidays). I’m looking forward to Christmas’ coming, when my university semester ends. But in this month, in parallel with this, I want to complete the following things:

• Kaggle micro-courses: Python (https://www.kaggle.com/learn/python)
Pandas(https://www.kaggle.com/learn/pandas)

There are more amazing courses such as "Data Visualization" or "Intermediate/Intro to Machine Learning", but I want to take them when my challenge will start =)

• M4ML - Linear Algebra

Playlist on youtube link: https://www.youtube.com/watch?v=T73ldK46JqE&list=PLiiljHvN6z1_o1ztXTKWPrShrMrBLo5P3

Course link: https://www.coursera.org/learn/linear-algebra-machine-learning

Excellent & extreme super performance! At the beginning of this year I chose this specialisation, but after ending this I’d stopped my learning by reason of the workload at the university and my extra language courses :c I want to repeat some of this knowledges. My plans include repeating them on YouTube channel. Maybe I’ll redo some of the exercises in my Coursera account.

• Mathematics, and more mathematics! Although Russian is my native language it is easier for me to courses about it on English, like the ones I gave above (lol), for instance. Nevertheless, there are difficult topics, and I go through them by http://mathprofi.ru/. Reading the articles of this cool dude in Russian is more comfortable for me than watching videos in this language.

• It’s much better to make a small plan and overfill it then write a huge one, fail it, and feel frustrated after this. However, I can’t remind myself about interesting problem collections, such as https://projecteuler.net/, where the key to the solution is in a mix of mathematic and programming.
Also I want to notice this course about python: https://stepik.org/course/67/promo. Tasks in it are quite complex, but at the same time interesting.

Well, I have presented to you my plan for the current month. Have fun!

Introduction?

Alex Maszański — Fri, 20 Nov 2020 19:24:07 +0000

In this blog I will try to describe my educational path in one of the most difficult areas of programming for me.
Moreover, this online resource is a way to improve my knowledge of English: D (at least I hope so)

I am Belarusian & Polish by birth, now I live in Tbilisi. I am studying philology at a local university (strange choice for a future data scientist LOL).
My humanitarian skills: Russian (free), Polish (A2 to B1), Georgian and Arabic (თითქმის).