TIETOJA TÄSTÄ JAKSOSTA
See the full show notes for this episode on the website at talkpython.fm/285
Englanti
Yhdysvallat
TRANSKRIPTIO 🔗
WEBVTT
00:00:00.001 --> 00:00:02.880
If you're into data science, you've probably heard about Dask.
00:00:02.880 --> 00:00:07.820
It's a package that feels like familiar APIs such as NumPy, Pandas, and scikit-learn.
00:00:07.820 --> 00:00:12.360
Yet it can scale that computation across CPU cores on your local machine
00:00:12.360 --> 00:00:16.440
all the way to distributed grid-based computing in large clusters.
00:00:16.440 --> 00:00:21.300
While powerful, this takes some setup to execute in it…
00:00:00.001 --> 00:00:02.880
If you're into data science, you've probably heard about Dask.
00:00:02.880 --> 00:00:07.820
It's a package that feels like familiar APIs such as NumPy, Pandas, and scikit-learn.
00:00:07.820 --> 00:00:12.360
Yet it can scale that computation across CPU cores on your local machine
00:00:12.360 --> 00:00:16.440
all the way to distributed grid-based computing in large clusters.
00:00:16.440 --> 00:00:21.300
While powerful, this takes some setup to execute in it…
HAE EDELLISIÄ EPISODEJA
Hae kanavan Talk Python To Me vanhoja jaksoja.
Vastuuvapautusilmoitus: Tälle sivulle upotettu podcast ja kuvitus ovat peräisin Michael Kennedy:ltä, joka on sen omistajan omaisuutta, eikä se ole sidoksissa Listen Notes, Inc:n tukemaan.
MUOKKAA
Kiitos, kun autoit pitämään podcast-tietokantaa ajan tasalla.
