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OR_on1141018077 |
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OCoLC |
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20231017213018.0 |
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vz czazuu |
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200218s2019 xx 051 o vleng d |
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|a UMI
|b eng
|e rda
|e pn
|c UMI
|d OCLCF
|d ERF
|d OCLCO
|d OCLCQ
|d OCLCO
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035 |
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|a (OCoLC)1141018077
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037 |
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|a CL0501000098
|b Safari Books Online
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050 |
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4 |
|a QA76.73.P98
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049 |
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|a UAMI
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245 |
0 |
0 |
|a Linear algebra for data science in Python /
|c 365 Careers.
|
264 |
|
1 |
|a [Place of publication not identified] :
|b Packt Publishing,
|c 2019.
|
300 |
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|a 1 online resource (1 streaming video file (50 min., 57 sec.))
|
336 |
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|a two-dimensional moving image
|b tdi
|2 rdacontent
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337 |
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|a computer
|b c
|2 rdamedia
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337 |
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|a video
|b v
|2 rdamedia
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338 |
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|a online resource
|b cr
|2 rdacarrier
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500 |
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|a Title from resource description page (Safari, viewed February 17, 2020).
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520 |
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|a "Vectorizing your code is an essential skill to make your calculations faster and take advantage of the capabilities of modern machine and deep learning packages. This course will get you up and running with linear algebra fundamentals for data science in Python. In this course, you will learn about scalars, vectors, and matrices and the geometrical meaning of these objects. You will also learn how you should use linear algebra in your Python code. In addition to this, you'll be able to perform operations such as addition, subtraction and dot product. As you cover further sections, you'll focus on the different syntactical errors you can encounter while vectorizing your code. By the end of this course, you will have gained the skills you need to use linear algebra confidently in your data science projects."--Resource description page
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590 |
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
|
650 |
|
0 |
|a Python (Computer program language)
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650 |
|
0 |
|a Vector processing (Computer science)
|
650 |
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0 |
|a Algebras, Linear
|x Data processing.
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650 |
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0 |
|a Machine learning.
|
650 |
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0 |
|a Research
|x Data processing.
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650 |
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6 |
|a Python (Langage de programmation)
|
650 |
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6 |
|a Traitement vectoriel.
|
650 |
|
6 |
|a Algèbre linéaire
|x Informatique.
|
650 |
|
6 |
|a Apprentissage automatique.
|
650 |
|
7 |
|a Algebras, Linear
|x Data processing.
|2 fast
|0 (OCoLC)fst00804949
|
650 |
|
7 |
|a Machine learning.
|2 fast
|0 (OCoLC)fst01004795
|
650 |
|
7 |
|a Python (Computer program language)
|2 fast
|0 (OCoLC)fst01084736
|
650 |
|
7 |
|a Research
|x Data processing.
|2 fast
|0 (OCoLC)fst01095179
|
650 |
|
7 |
|a Vector processing (Computer science)
|2 fast
|0 (OCoLC)fst01164669
|
655 |
|
4 |
|a Electronic videos.
|
710 |
2 |
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|a 365 Careers,
|e author.
|
710 |
2 |
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|a Packt Publishing,
|e publisher.
|
856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9781839214219/?ar
|z Texto completo (Requiere registro previo con correo institucional)
|
994 |
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|a 92
|b IZTAP
|