April 2024
Intermediate to advanced
398 pages
11h 1m
Polish
book
Uczenie maszynowe w Pythonie. Receptury. Od przygotowania danych do deep learningu.
by Kyle Gallatin, Chris Albon
Content preview from Uczenie maszynowe w Pythonie. Receptury. Od przygotowania danych do deep learningu.
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Rozdział 4. Obsługa danych liczbowych
4.0. Wprowadzenie
Dane ilościowe pozwalają na pomiar wielkości dowolnych elementów: klasy, miesięcznej sprzedaży lub ocen uczniów. Naturalnym sposobem na przedstawienie tego pomiaru jest użycie liczb, na przykład 29 uczniów lub sprzedaż w wysokości 529 392 zł. W rozdziale przedstawię wiele strategii z zakresu przekształcania surowych danych liczbowych na cechy wykorzystywane później w algorytmach uczenia maszynowego.
4.1. Przeskalowywanie cechy
Problem
Musisz przeskalować wartości cech liczbowych w taki sposób, aby mieściły się w przedziale wyznaczonym przez dwie wartości.
Rozwiązanie
Do przeskalowania tablicy cech użyj oferowanej przez bibliotekę scikit-learn klasy MinMaxScaler.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.