Last updated on: 18/12/2020
Well, maybe I’m not as popular to be frequently asked about all these things; however, you can treat this page more like an aggregator for some of my handy answers.
If you have a question that was not listed on this page, please do not hesitate to get in touch with me. I will also try to let myself be known in different posts and pages of this blog.
People change on average every 7 years (I think), that is why I keep the “Last Updated” note above to indicate that an answer could have been modified or added.
- Why did you start this blog?
I tried to answer this question in depth in my first post.
Briefly speaking, I enjoy writing, and I would feel unfulfilled keeping all the exciting stuff locked in my mind without sharing it with someone who might greatly benefit from it.
- What is your life goal/direction?
To be happy with what I do for the living and contribute as much as I can to the constantly developing world, leaving the universe in a better state in the end.
- Your motto?
“Try to be the best version of yourself“.
I also keep “Done is better than perfect“ close to my heart, to ease my fight with procrastination and perfectionism.
You can find the list of all my favourite thoughts here (updated regularly).
- Answer in one word: What is the must-have for success?
- Places you are actively visible online?
In a nutshell, you can hear from me on:
• My blog <— website hosting all this text. Sign up to my newsletter not to miss anything new!
• Facebook Fan page <— notifications on new blog posts, book reviews, summaries of engaging podcasts, and more
• Twitter <— nowadays, my favourite social platform. Besides all the social interaction, it includes the content shared on the FB fan page
• LinkedIn <— discussions with my employers accompanied by exclusive articles shared on my profile
• GitHub <— technical contributions through own repositories and collaborations to the other public ones
• Instagram <— visual presence (chiefly on my stories) with lots of well-categorised highlights
• Goodreads <— my online library. Inspire yourself with all the books I’m reading, follow my reviews and annotations to the e-books consumed on my Kindle
• Hypothes.is <— annotations/highlights of the online articles I step on
• Pinterest <— database of infographics regarding all my areas of interest
• Reddit <— 2nd most favourite social platform after Twitter thanks to its subreddits
• SoundCloud <— #1 entertainment website. I’m actively researching new tunes and at some point publishing my own sounds
• Last.fm <— archive of my musical taste (since 2012)
Don’t forget that you can always find my most quintessential profiles in the header of this website.
- Who are your life influencers and why?
• Mike Shinoda <— for the overall lifestyle, kindness and performance in one of my favourite bands – Linkin Park
• Elon Musk <— for all the input to engineering and staying loose while being on the top
• Andrej Karpathy <— for his contribution to driverless cars at Tesla
• Grant Sanderson <— for encouraging me in learning math and clearly presenting calculus topics
• Andrew Ng <— for teaching me the patience to learn machine learning
• Yann LeCun <— for his contribution to computer vision (CNN)
• Daniel Bourke <— for sharing a motivation to keep practising machine learning while maintaining a healthy lifestyle
• Lex Fridman <— for the way he expresses an interest in such a broad variety of topics while hosting the discussions on his podcast
• Victor Zhou & Jay Alammar <— for the way of explaining machine learning topics in their blog posts
• Tania Rascia <— for presenting a clear and visually pleasing way of web development
• Ali Abdaal <— for the way of staying organised and charming to his viewers. Don’t know if I ever found someone more structured
• Jordan B Peterson <— for teaching me how to think of almost every life aspect
• Gary Vaynerchuk <— for giving me the courage to act
• Tim Ferris <— for inspiring so many of us through his lifestyle
• Grant Cardone <— for teaching me how to be fearless of business/marketing
• Felix Kjellberg <— for showing how not to take everything too seriously
• Jakub Mrugalski (🇵🇱) <— for sharing all the engaging content and showing the right approach to interact with the online community
• Adrian Olszewski (🇵🇱) <— for his in-depth knowledge on statistical topics and patience in teaching others throughout LinkedIn
• Mirosław Zelent (🇵🇱) <— for guiding me in making my first steps in programming
• Łukasz Prokulski (🇵🇱) <— for explaining so many different use cases of data analysis
• Kamil J. Dudek (🇵🇱) <— for his eloquent writing style and knowledge about tech
• Mirosław Burnejko (🇵🇱) <— for motivating me and showing every step of his early entrepreneurship through daily YouTube vlogs
• Maciej Aniserowicz (🇵🇱) <— for doing the same as Mirosław Burnejko, but more inside the programming sphere
• Andrzej Krzywda (🇵🇱) <— for the encouragement to start this blog
- Let’s get a bit more technical. What do you prefer: Python, R or maybe something else?
I always say that in data science it’s the most important to excel in logic and statistical familiarity. Later, the language is like a suit you wear, and in my case, I mostly reach for Python. I found many senior R developers, who claimed that they would start with Python if they got another chance (mainly for the reason of ML-based resources); however, I’m jealous of their pretty looking RStudio.
Once I found a great comparison between the languages in a single presentation, which might give you a clear contrast between both options.
You may also want to try and combine both languages to use the best part of each. This blog post should explain how to do it most conveniently.
• (R) reticulate for connecting R with Python
• (R) tidyverse for data exploration
• (Python) scikit-learn/TensorFlow/PyTorch for ML and DL
• (R) ggplot2 for visualisation
• (R) R Markdown for reporting and Shiny for web apps
Apart from these technologies, we need to keep our heads up for the rapid intake of Julia and Scala, which seem to be more optimised over Python.
- IDE for data science?
Jupyter Notebook for research and effortless maintenance of a well-documented and testable code. Moreover, it runs in a browser and nicely displays your pretty visualisations, which makes it stand out for data science.
On the other side, I enjoyed using classical Sublime Text for its speed, but nowadays, I switched over to VS Code, which gets pretty decent reviews, especially from the Pythonic community.
If you are not happy with those, you can also try Spyder as a free solution and PyCharm for even more professional (production like) development.
If you want to try Jupyter, Spyder and VS Code, just install a famous Anaconda Distribution to have a clear overview and ease of management over your tools.
Edit: Recently, Google Colaboratory is a more and more popular choice that requires no setup and runs entirely in the cloud. As such, it is one of the best free options for running large deep learning models (don’t forget to change the runtime type to GPU/TPU).
- Can you also recommend me XYZ (blogs, tools, data science resources, programming learning materials, etc.)?
Sure, have a look at my great list of recommendations.
- What books are you currently reading? Do you publish some reviews?
Of course, you can check my reading progress and the reviews on my Goodreads profile. I am also spending a lot of time with online materials and annotating them with my Hypothes.is account.
- Favourite entertainment website?
SoundCloud for music and Twitter/Hackernews for online discussions. Talking about SoundCloud, I realised it is not only my main entertainment website since 2012 but a permanent source of joy through everyday fresh tunes that I like. Thanks to this orange cloud, I could find many artists, friends and sources of influence, such as CruciA, synx and Souhex, who play a huge part in my life.
In my free time, I want to be more active on the site and start sharing more of my own creations.
- Favourite TV show?
I don’t usually watch any TV series, but Mr. Robot gave me a lot of a great time of reflection.
- I want to be like you or XYZ?
Don’t waste your time trying to be like anyone else. Moreover, do not compare yourself to others as you can only harm yourself this way. Let yourself have some influencers, but do not copy them. Everyone is beautiful in their being, and this is why the world can advance, by brainstorming through unique views and forming exceptional solutions.
- I love your content a ton! Can I support you anywhere?
You already mean a lot to me by sticking around to my online persona! However, if you’re such a determined and lovely person, you can drop me a donation on my PayPal account.