MLflow — A platform for the machine learning lifecycle An open-source platform for the machine learning lifecycle MLflow

So let’s go with the latter one. At first, I manually extracted the minority class and repeated it until we have a more or less similar count. I noticed that it’s not efficient. If I try to do it per one dimension value, I quickly get lost. As usual with python, I thought there has to be a library for this.

As I type this, I have four different tabs open to Amazon. It’s Prime Day, I need a new microwave, and as someone who treats bargain hunting like a competitive sport, I’ve been preparing for today like an athlete before the championship game.

“None of this means you’re a sucker for filling your cart,” Morgan writes, but “with a list and a clear mind, you can take advantage of the sale, instead of letting it take advantage of you.”

The most common (or at least it was for me) understanding that sklearn is the most used library for ML. Before going to baseline results, I’m going to present some of the libraries. Keep in mind I’m aiming here at fresh Data Scientist or this path explorers, so I’m not going to Neural Network libraries (Keras, Tensorflow, PyTorch).

GetX. I’m not a fan of GetX. GetX tries to get a lot done, which limits your flexibility. If you’re going for a “Full App” package, then GetX is the way to go. I’ve tried it and didn’t like it — but if it’s what works for you, then great!

Now your data preparation will be robust, and you will be sure that your train dataset and the one you’ll be basing your predictions will follow the same manipulations in the same order!

“None of this means you’re a sucker for filling your cart,” Morgan writes, but “with a list and a clear mind, you can take advantage of the sale, instead of letting it take advantage of you.”

And apparently there was! Library imblearn is dedicated to help you solve this issue! You can choose different methods of oversampling, under-sampling, or even a combination of them.

Which is exactly the point. As Kate Morgan explains, quick sales like Prime Day are designed to hack our brains, tapping into scarcity bias (valuing something more when there’s a limited supply) and social proof bias (believing that just because hundreds of people did or bought something, it must be good).

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ed waking up at least an hour earlier than usual to read. What I’ve found is that end of a reading session, even just an hour, my mind becomes impregnated with a flood of ideas, my perspectives shift, and my beliefs are either challenged or reinforced.

redux / fish_redux / mobx: These all came from React, and have very similar styles — but I think that it quickly becomes clear that React and Flutter are two different but similar beasts. These work, and if you’re used to them, then you can use them, but the state management designed for Flutter work the most cleanly, in my opinion.

get_it: It says it right on the box. get_it is not a state management solution — but people keep using it like one. It’s very messy if used as a state management solution, and you honestly might be better off just declaring floating variables in files.

RiverPod is just Provider in a different skin — a sleeker, better skin. If you’re starting a new app and want to go the Provider route, I highly recommend you consider RiverPod.

Compile Safety: This is, by far, the best innovation to come to state management. If your code compiles, you’re good. No longer are we going to wonder why we can’t find our provider in the tree. This is an innovation that is huge and will save you so, so much time.

redux / fish_redux / mobx: These all came from React, and have very similar styles — but I think that it quickly becomes clear that React and Flutter are two different but similar beasts. These work, and if you’re used to them, then you can use them, but the state management designed for Flutter work the most cleanly, in my opinion.