The complete machine learning cource with Python:
"Inside the course, you'll learn how to: set up a Python development environment correctly; gain complete machine learning toolsets to tackle most real-world problems; understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accu...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Weitere beteiligte Personen: | |
| Format: | Elektronisch Video |
| Sprache: | Englisch |
| Veröffentlicht: |
[Place of publication not identified]
Packt Publishing
2018
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781789953725/?ar |
| Zusammenfassung: | "Inside the course, you'll learn how to: set up a Python development environment correctly; gain complete machine learning toolsets to tackle most real-world problems; understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them; combine multiple models with by bagging, boosting or stacking; make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data; develop in Jupyter (IPython) notebook, Spyder and various IDE; communicate visually and effectively with Matplotlib and Seaborn; engineer new features to improve algorithm predictions; make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data; use SVM for handwriting recognition, and classification problems in general; use decision trees to predict staff attrition; apply the association rule to retail shopping datasets."--Resource description page |
| Beschreibung: | Title from resource description page (Safari, viewed January 8, 2019) |
| Umfang: | 1 Online-Ressource (1 streaming video file (18 hr., 22 min., 46 sec.)) |
| ISBN: | 1789953723 9781789953725 |
Internformat
MARC
| LEADER | 00000cgm a22000002 4500 | ||
|---|---|---|---|
| 001 | ZDB-30-ORH-047732997 | ||
| 003 | DE-627-1 | ||
| 005 | 20240228120628.0 | ||
| 006 | m o | | | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 191023s2018 xx ||| |o o ||eng c | ||
| 020 | |a 1789953723 |9 1-78995-372-3 | ||
| 020 | |a 9781789953725 |9 978-1-78995-372-5 | ||
| 020 | |a 9781789953725 |9 978-1-78995-372-5 | ||
| 035 | |a (DE-627-1)047732997 | ||
| 035 | |a (DE-599)KEP047732997 | ||
| 035 | |a (ORHE)9781789953725 | ||
| 035 | |a (DE-627-1)047732997 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 100 | 1 | |a Ng, Anthony |e RednerIn |4 spk | |
| 245 | 1 | 4 | |a The complete machine learning cource with Python |c Anthony NG, Rob Percival |
| 264 | 1 | |a [Place of publication not identified] |b Packt Publishing |c 2018 | |
| 300 | |a 1 Online-Ressource (1 streaming video file (18 hr., 22 min., 46 sec.)) | ||
| 336 | |a zweidimensionales bewegtes Bild |b tdi |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Title from resource description page (Safari, viewed January 8, 2019) | ||
| 520 | |a "Inside the course, you'll learn how to: set up a Python development environment correctly; gain complete machine learning toolsets to tackle most real-world problems; understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them; combine multiple models with by bagging, boosting or stacking; make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data; develop in Jupyter (IPython) notebook, Spyder and various IDE; communicate visually and effectively with Matplotlib and Seaborn; engineer new features to improve algorithm predictions; make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data; use SVM for handwriting recognition, and classification problems in general; use decision trees to predict staff attrition; apply the association rule to retail shopping datasets."--Resource description page | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Machine learning | |
| 650 | 4 | |a Python (Langage de programmation) | |
| 650 | 4 | |a Apprentissage automatique | |
| 650 | 4 | |a Machine learning |0 (OCoLC)fst01004795 | |
| 650 | 4 | |a Python (Computer program language) |0 (OCoLC)fst01084736 | |
| 650 | 4 | |a Electronic videos | |
| 700 | 1 | |a Percival, Rob |e VerfasserIn |4 aut | |
| 776 | 1 | |z 1789953723 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 1789953723 |
| 966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781789953725/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
| 912 | |a ZDB-30-ORH | ||
| 935 | |c vide | ||
| 951 | |a BO | ||
| 912 | |a ZDB-30-ORH | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-30-ORH-047732997 |
|---|---|
| _version_ | 1821494949022007296 |
| adam_text | |
| any_adam_object | |
| author | Percival, Rob |
| author2 | Ng, Anthony |
| author2_role | spk |
| author2_variant | a n an |
| author_facet | Percival, Rob Ng, Anthony |
| author_role | aut |
| author_sort | Percival, Rob |
| author_variant | r p rp |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-30-ORH |
| ctrlnum | (DE-627-1)047732997 (DE-599)KEP047732997 (ORHE)9781789953725 |
| format | Electronic Video |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02865cgm a22004812 4500</leader><controlfield tag="001">ZDB-30-ORH-047732997</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240228120628.0</controlfield><controlfield tag="006">m o | | </controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">191023s2018 xx ||| |o o ||eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1789953723</subfield><subfield code="9">1-78995-372-3</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781789953725</subfield><subfield code="9">978-1-78995-372-5</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781789953725</subfield><subfield code="9">978-1-78995-372-5</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047732997</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP047732997</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781789953725</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047732997</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ng, Anthony</subfield><subfield code="e">RednerIn</subfield><subfield code="4">spk</subfield></datafield><datafield tag="245" ind1="1" ind2="4"><subfield code="a">The complete machine learning cource with Python</subfield><subfield code="c">Anthony NG, Rob Percival</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Place of publication not identified]</subfield><subfield code="b">Packt Publishing</subfield><subfield code="c">2018</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (1 streaming video file (18 hr., 22 min., 46 sec.))</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">zweidimensionales bewegtes Bild</subfield><subfield code="b">tdi</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Title from resource description page (Safari, viewed January 8, 2019)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">"Inside the course, you'll learn how to: set up a Python development environment correctly; gain complete machine learning toolsets to tackle most real-world problems; understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them; combine multiple models with by bagging, boosting or stacking; make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data; develop in Jupyter (IPython) notebook, Spyder and various IDE; communicate visually and effectively with Matplotlib and Seaborn; engineer new features to improve algorithm predictions; make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data; use SVM for handwriting recognition, and classification problems in general; use decision trees to predict staff attrition; apply the association rule to retail shopping datasets."--Resource description page</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python (Langage de programmation)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Apprentissage automatique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield><subfield code="0">(OCoLC)fst01004795</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python (Computer program language)</subfield><subfield code="0">(OCoLC)fst01084736</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electronic videos</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Percival, Rob</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="1" ind2=" "><subfield code="z">1789953723</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">1789953723</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781789953725/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="935" ind1=" " ind2=" "><subfield code="c">vide</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-30-ORH-047732997 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:22:30Z |
| institution | BVB |
| isbn | 1789953723 9781789953725 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (1 streaming video file (18 hr., 22 min., 46 sec.)) |
| psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | Packt Publishing |
| record_format | marc |
| spelling | Ng, Anthony RednerIn spk The complete machine learning cource with Python Anthony NG, Rob Percival [Place of publication not identified] Packt Publishing 2018 1 Online-Ressource (1 streaming video file (18 hr., 22 min., 46 sec.)) zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Title from resource description page (Safari, viewed January 8, 2019) "Inside the course, you'll learn how to: set up a Python development environment correctly; gain complete machine learning toolsets to tackle most real-world problems; understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them; combine multiple models with by bagging, boosting or stacking; make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data; develop in Jupyter (IPython) notebook, Spyder and various IDE; communicate visually and effectively with Matplotlib and Seaborn; engineer new features to improve algorithm predictions; make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data; use SVM for handwriting recognition, and classification problems in general; use decision trees to predict staff attrition; apply the association rule to retail shopping datasets."--Resource description page Python (Computer program language) Machine learning Python (Langage de programmation) Apprentissage automatique Machine learning (OCoLC)fst01004795 Python (Computer program language) (OCoLC)fst01084736 Electronic videos Percival, Rob VerfasserIn aut 1789953723 Erscheint auch als Druck-Ausgabe 1789953723 |
| spellingShingle | Percival, Rob The complete machine learning cource with Python Python (Computer program language) Machine learning Python (Langage de programmation) Apprentissage automatique Machine learning (OCoLC)fst01004795 Python (Computer program language) (OCoLC)fst01084736 Electronic videos |
| subject_GND | (OCoLC)fst01004795 (OCoLC)fst01084736 |
| title | The complete machine learning cource with Python |
| title_auth | The complete machine learning cource with Python |
| title_exact_search | The complete machine learning cource with Python |
| title_full | The complete machine learning cource with Python Anthony NG, Rob Percival |
| title_fullStr | The complete machine learning cource with Python Anthony NG, Rob Percival |
| title_full_unstemmed | The complete machine learning cource with Python Anthony NG, Rob Percival |
| title_short | The complete machine learning cource with Python |
| title_sort | complete machine learning cource with python |
| topic | Python (Computer program language) Machine learning Python (Langage de programmation) Apprentissage automatique Machine learning (OCoLC)fst01004795 Python (Computer program language) (OCoLC)fst01084736 Electronic videos |
| topic_facet | Python (Computer program language) Machine learning Python (Langage de programmation) Apprentissage automatique Electronic videos |
| work_keys_str_mv | AT nganthony thecompletemachinelearningcourcewithpython AT percivalrob thecompletemachinelearningcourcewithpython AT nganthony completemachinelearningcourcewithpython AT percivalrob completemachinelearningcourcewithpython |