zweidimensionales bewegtes Bild
Testable ML Data Science: How to make numeric code testable using Scikit-Learn's interfaces.
- Weitere Titel
-
Using Scikit-Learn's interface for turning Spaghetti Data Science into Maintainable Software
- Standort
-
Hannover TIB
- Umfang
-
197MB, 00:32:51:00 (unknown)
- Sprache
-
Englisch
- Anmerkungen
-
Audiovisuelles Material
- Erschienen in
-
EuroPython 2015 ; Vol. 37, (Jan. 2015)
- Schlagwort
-
EP 2015
EuroPython Conference
EuroPython 2015
- Ereignis
-
Veröffentlichung
- (wer)
-
EuroPython
- (wann)
-
2015-01-01
- Beteiligte Personen und Organisationen
-
Peters, Holger
- DOI
-
10.5446/20215
- Letzte Aktualisierung
-
04.12.2024, 08:09 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Technische Informationsbibliothek (TIB). Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Technische Informationsbibliothek (TIB). Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- zweidimensionales bewegtes Bild
Beteiligte
- Peters, Holger
- EuroPython
Entstanden
- 2015-01-01
Ähnliche Objekte (12)
Scikit-learn to "learn them all"
Learn Python The Fun Way
What can python learn from Haskell?
Extending Scikit-Learn with your own Regressor
What Python can learn from Haskell packaging
Productionizing your ML code seamlessly
Can Rust make Python shine?
Building a Naive Bayes Text Classifier with scikit-learn
Building Service interfaces with OpenAPI / Swagger
IPython: The Productivity Booster: Learn to be productive with IPython
How to make IT-recruiting suck less.
How can you use Open Source materials to learn Python & data science?
Scikit-learn to "learn them all"
Learn Python The Fun Way
What can python learn from Haskell?
Extending Scikit-Learn with your own Regressor
What Python can learn from Haskell packaging
Productionizing your ML code seamlessly
Can Rust make Python shine?
Building a Naive Bayes Text Classifier with scikit-learn
Building Service interfaces with OpenAPI / Swagger
IPython: The Productivity Booster: Learn to be productive with IPython
How to make IT-recruiting suck less.
How can you use Open Source materials to learn Python & data science?
Scikit-learn to "learn them all"
Learn Python The Fun Way
What can python learn from Haskell?
Extending Scikit-Learn with your own Regressor
What Python can learn from Haskell packaging
Productionizing your ML code seamlessly
Can Rust make Python shine?
Building a Naive Bayes Text Classifier with scikit-learn
Building Service interfaces with OpenAPI / Swagger
IPython: The Productivity Booster: Learn to be productive with IPython
How to make IT-recruiting suck less.