Levi

R² is a widely used measure of fit, but for many analysts, it is just a number. They believe high R² ➡ Good predictions. This is not always true! Now I will clarify. 🔽 R-squared measures how well the regression model fits the observed data. To be more precise: It is the proportion of the variation in the dependent variable that is predictable from the independent variable. It usually ranges from 0 to 1: (In rare cases it can be negative, I will explain this in another tweet) R² = 0 The model does not explain any of the variability in the dependent variable ➡ No predictive power ➡ Bad model. R² = 1 The model perfectly explains all the variability in the dependent variable ➡ Perfect fit to the data ➡ Good model if not overfitted and has predictive power. A high R-squared value does not mean that the predictions made by the model will be correct. It doesn't measure predictability power, it measures how well the model fits! In the example below, we compare the mean of the data to a fitted line. Of course, the mean of values is not a good fit ➡ the errors are large. On the other hand, the fitted line has smaller errors ➡ The R² will be close to 1. To calculate R² we need: - The total sum of squares for the mean - Sum of squares for the residuals from the model - Finally, subtract the ratio from 1 ___ That's it for today. I hope you've found this Tweet helpful. Like/Retweet for support and follow @levikul09 for more Data Science content. Thanks 😉

@pawjast @freeCodeCamp If you already use markdown then obsidian will be easy to move to. It's way more customizable and clutter free. Of course there are use cases where notion is better, put you will probably find a plug in that will achieve a similar thing.

Now that you've mentioned it I will have a look at Obsidian. In my case I think specifically I've first heard of of notion and started using it (before I was making notes in markdown files and kept them on github) and only later I've come across Obsidian (but since Notion works for me I had no incentive to change for the sake of changing).

Stop using Notion like a basic notebook. Make it your personal operating system. In this massive 12-hour course, you'll learn about formulas and automations, how to build databases, productivity systems, dashboards, and much more, all inside of Notion. freecodecamp.org/news/lean-noti…

@pawjast @freeCodeCamp It's the other way around for me. I am an obsidian lover and wannabe Linux guy.

@levikul09 @freeCodeCamp I can't do it all. Perhaps my obsidian days are still ahead of me but notion is enough for now:)

@pawjast @freeCodeCamp You use Linux but not obsidian? I thought they go hand in hand 😄

@freeCodeCamp 12 hours to learn Notion?!?! I clearly am missing some of the functionality (like 99% of it) at the moment 😅.

My copy is finally here!

@pawjast Why not vim in vsc? What emacs can do above that combination?

@levikul09 I am actually inspired now to perhaps try something else, more text based like perhaps Emacs. But at the same time VSC is fairly flexible, has a lot of good shortcuts and allows custom mapping as well so I might be better off spending more time refining my VSC skill...

In the world of vibe coding it was very refreshing to listen to these two guys talking about the importance of spending the time to learn the tool you use every day that is your code editor. Tweak the settings, learn the shortcuts, learn how to code without looking at the keyboard so nothing gets in the way of your coding and you can just flow. For hours.

@pawjast I found this today. Looks cool and the community is growing, I see some folks use it for coding. I might try it out. That's next level speed they do with it. youtu.be/PBIRwBOIJ-8?si…

@pawjast Yeah, same for me actually , laptop, windows, vs code but with external screen and keyboard. I tried vim motions but the learning curve is steep. It would be great for writing as well in obsidian. I have some macros in Ahk for productivity though.

@pawjast And what about editor? Are you a vim master like prime?

@levikul09 Very poor at the moment. I work off my laptop but without any extra monitors or keyboards. But I'll probably make some changes soon. How about you?

Conditional probability is the single most important concept in statistics. Why? Because without accounting for prior information, predictive models are useless. Here is what conditional probability is, and why it is essential.

How to build a good understanding of math for machine learning? I get this question a lot, so I decided to make a complete roadmap for you. In essence, three fields make this up: calculus, linear algebra, and probability theory. Let's take a quick look at them!

Four years ago, I started a project that turned out to be life-altering, and it has just passed a huge milestone. I'm happy to announce that my Mathematics of Machine Learning book will soon be published by Packt Publishing! Yes, there will be a physical version.

@svpino How do you like it compared to codeium?

Copilot is now free! Probably the biggest news for developers in 2024.

I share similar tips in my newsletter: Data Ground Up. Link in bio. You can read the full article there and sign up for similar posts.

But when to use it then? 1️⃣ For quick explorations 2️⃣ Using star to reference rows.

SELECT * is the "Hello World" of SQL. But it's a trap. You should avoid it. Here’s why 👇