Learning data mining with Python use Python to manipulate data and build predictive models
Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Getting Started with Data Mining -- Introducing data mining -- Using Python and the Jupyter Notebook -- Installing Python -- Installing Jupyt...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing
2017
|
| Ausgabe: | Second edition |
| Schlagworte: | |
| Online-Zugang: | BTW01 Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
MARC
| LEADER | 00000nmm a22000001c 4500 | ||
|---|---|---|---|
| 001 | BV049383492 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 231026s2017 |||| o||u| ||||||eng d | ||
| 020 | |a 9781787129566 |c ebook |9 978-1-78712-956-6 | ||
| 035 | |a (OCoLC)1409115637 | ||
| 035 | |a (DE-599)KEP014924765 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-526 | ||
| 082 | 0 | |a 5.133 | |
| 084 | |a ST 250 |0 (DE-625)143626: |2 rvk | ||
| 100 | 1 | |a Layton, Robert |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Learning data mining with Python |b use Python to manipulate data and build predictive models |c Robert Layton |
| 250 | |a Second edition | ||
| 264 | 1 | |a Birmingham |b Packt Publishing |c 2017 | |
| 300 | |a 1 online resource (348 pages) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | 3 | |a Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Getting Started with Data Mining -- Introducing data mining -- Using Python and the Jupyter Notebook -- Installing Python -- Installing Jupyter Notebook -- Installing scikit-learn -- A simple affinity analysis example -- What is affinity analysis? -- Product recommendations -- Loading the dataset with NumPy -- Downloading the example code -- Implementing a simple ranking of rules -- Ranking to find the best rules -- A simple classification example -- What is classification? -- Loading and preparing the dataset -- Implementing the OneR algorithm -- Testing the algorithm -- Summary -- Chapter 2: Classifying with scikit-learn Estimators -- scikit-learn estimators -- Nearest neighbors -- Distance metrics -- Loading the dataset -- Moving towards a standard workflow -- Running the algorithm -- Setting parameters -- Preprocessing -- Standard pre-processing -- Putting it all together -- Pipelines -- Summary -- Chapter 3: Predicting Sports Winners with Decision Trees -- Loading the dataset -- Collecting the data -- Using pandas to load the dataset -- Cleaning up the dataset -- Extracting new features -- Decision trees -- Parameters in decision trees -- Using decision trees -- Sports outcome prediction -- Putting it all together -- Random forests -- How do ensembles work? -- Setting parameters in Random Forests -- Applying random forests -- Engineering new features -- Summary -- Chapter 4: Recommending Movies Using Affinity Analysis -- Affinity analysis -- Algorithms for affinity analysis -- Overall methodology -- Dealing with the movie recommendation problem -- Obtaining the dataset -- Loading with pandas -- Sparse data formats -- Understanding the Apriori algorithm and its implementation. | |
| 650 | 0 | 7 | |a Python |g Programmiersprache |0 (DE-588)4434275-5 |2 gnd |9 rswk-swf |
| 653 | 0 | |a Python (Computer program language) | |
| 653 | 0 | |a Python (Computer program language) | |
| 653 | 0 | |a Electronic books | |
| 689 | 0 | 0 | |a Python |g Programmiersprache |0 (DE-588)4434275-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 856 | 4 | 0 | |m X:EBC |u https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=4851656 |x Verlag |3 Volltext |
| 912 | |a ZDB-30-PQE | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034711063 | ||
| 966 | e | |u https://ebookcentral.proquest.com/lib/th-wildau/detail.action?docID=4851656 |l BTW01 |p ZDB-30-PQE |q BTW_PDA_PQE_KAUF |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804186087297384448 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Layton, Robert |
| author_facet | Layton, Robert |
| author_role | aut |
| author_sort | Layton, Robert |
| author_variant | r l rl |
| building | Verbundindex |
| bvnumber | BV049383492 |
| classification_rvk | ST 250 |
| collection | ZDB-30-PQE |
| ctrlnum | (OCoLC)1409115637 (DE-599)KEP014924765 |
| dewey-full | 5.133 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 5.133 |
| dewey-search | 5.133 |
| dewey-sort | 15.133 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| edition | Second edition |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03364nmm a22004091c 4500</leader><controlfield tag="001">BV049383492</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">231026s2017 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781787129566</subfield><subfield code="c">ebook</subfield><subfield code="9">978-1-78712-956-6</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1409115637</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP014924765</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-526</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">5.133</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 250</subfield><subfield code="0">(DE-625)143626:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Layton, Robert</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Learning data mining with Python</subfield><subfield code="b">use Python to manipulate data and build predictive models</subfield><subfield code="c">Robert Layton</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">Second edition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham</subfield><subfield code="b">Packt Publishing</subfield><subfield code="c">2017</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (348 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Getting Started with Data Mining -- Introducing data mining -- Using Python and the Jupyter Notebook -- Installing Python -- Installing Jupyter Notebook -- Installing scikit-learn -- A simple affinity analysis example -- What is affinity analysis? -- Product recommendations -- Loading the dataset with NumPy -- Downloading the example code -- Implementing a simple ranking of rules -- Ranking to find the best rules -- A simple classification example -- What is classification? -- Loading and preparing the dataset -- Implementing the OneR algorithm -- Testing the algorithm -- Summary -- Chapter 2: Classifying with scikit-learn Estimators -- scikit-learn estimators -- Nearest neighbors -- Distance metrics -- Loading the dataset -- Moving towards a standard workflow -- Running the algorithm -- Setting parameters -- Preprocessing -- Standard pre-processing -- Putting it all together -- Pipelines -- Summary -- Chapter 3: Predicting Sports Winners with Decision Trees -- Loading the dataset -- Collecting the data -- Using pandas to load the dataset -- Cleaning up the dataset -- Extracting new features -- Decision trees -- Parameters in decision trees -- Using decision trees -- Sports outcome prediction -- Putting it all together -- Random forests -- How do ensembles work? -- Setting parameters in Random Forests -- Applying random forests -- Engineering new features -- Summary -- Chapter 4: Recommending Movies Using Affinity Analysis -- Affinity analysis -- Algorithms for affinity analysis -- Overall methodology -- Dealing with the movie recommendation problem -- Obtaining the dataset -- Loading with pandas -- Sparse data formats -- Understanding the Apriori algorithm and its implementation.</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Python</subfield><subfield code="g">Programmiersprache</subfield><subfield code="0">(DE-588)4434275-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Electronic books</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Python</subfield><subfield code="g">Programmiersprache</subfield><subfield code="0">(DE-588)4434275-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="m">X:EBC</subfield><subfield code="u">https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=4851656</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034711063</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/th-wildau/detail.action?docID=4851656</subfield><subfield code="l">BTW01</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">BTW_PDA_PQE_KAUF</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV049383492 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T22:59:36Z |
| indexdate | 2024-07-10T10:05:33Z |
| institution | BVB |
| isbn | 9781787129566 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034711063 |
| oclc_num | 1409115637 |
| open_access_boolean | |
| owner | DE-526 |
| owner_facet | DE-526 |
| physical | 1 online resource (348 pages) |
| psigel | ZDB-30-PQE ZDB-30-PQE BTW_PDA_PQE_KAUF |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Packt Publishing |
| record_format | marc |
| spelling | Layton, Robert Verfasser aut Learning data mining with Python use Python to manipulate data and build predictive models Robert Layton Second edition Birmingham Packt Publishing 2017 1 online resource (348 pages) txt rdacontent c rdamedia cr rdacarrier Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Getting Started with Data Mining -- Introducing data mining -- Using Python and the Jupyter Notebook -- Installing Python -- Installing Jupyter Notebook -- Installing scikit-learn -- A simple affinity analysis example -- What is affinity analysis? -- Product recommendations -- Loading the dataset with NumPy -- Downloading the example code -- Implementing a simple ranking of rules -- Ranking to find the best rules -- A simple classification example -- What is classification? -- Loading and preparing the dataset -- Implementing the OneR algorithm -- Testing the algorithm -- Summary -- Chapter 2: Classifying with scikit-learn Estimators -- scikit-learn estimators -- Nearest neighbors -- Distance metrics -- Loading the dataset -- Moving towards a standard workflow -- Running the algorithm -- Setting parameters -- Preprocessing -- Standard pre-processing -- Putting it all together -- Pipelines -- Summary -- Chapter 3: Predicting Sports Winners with Decision Trees -- Loading the dataset -- Collecting the data -- Using pandas to load the dataset -- Cleaning up the dataset -- Extracting new features -- Decision trees -- Parameters in decision trees -- Using decision trees -- Sports outcome prediction -- Putting it all together -- Random forests -- How do ensembles work? -- Setting parameters in Random Forests -- Applying random forests -- Engineering new features -- Summary -- Chapter 4: Recommending Movies Using Affinity Analysis -- Affinity analysis -- Algorithms for affinity analysis -- Overall methodology -- Dealing with the movie recommendation problem -- Obtaining the dataset -- Loading with pandas -- Sparse data formats -- Understanding the Apriori algorithm and its implementation. Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Python (Computer program language) Electronic books Python Programmiersprache (DE-588)4434275-5 s DE-604 X:EBC https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=4851656 Verlag Volltext |
| spellingShingle | Layton, Robert Learning data mining with Python use Python to manipulate data and build predictive models Python Programmiersprache (DE-588)4434275-5 gnd |
| subject_GND | (DE-588)4434275-5 |
| title | Learning data mining with Python use Python to manipulate data and build predictive models |
| title_auth | Learning data mining with Python use Python to manipulate data and build predictive models |
| title_exact_search | Learning data mining with Python use Python to manipulate data and build predictive models |
| title_exact_search_txtP | Learning data mining with Python use Python to manipulate data and build predictive models |
| title_full | Learning data mining with Python use Python to manipulate data and build predictive models Robert Layton |
| title_fullStr | Learning data mining with Python use Python to manipulate data and build predictive models Robert Layton |
| title_full_unstemmed | Learning data mining with Python use Python to manipulate data and build predictive models Robert Layton |
| title_short | Learning data mining with Python |
| title_sort | learning data mining with python use python to manipulate data and build predictive models |
| title_sub | use Python to manipulate data and build predictive models |
| topic | Python Programmiersprache (DE-588)4434275-5 gnd |
| topic_facet | Python Programmiersprache |
| url | https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=4851656 |
| work_keys_str_mv | AT laytonrobert learningdataminingwithpythonusepythontomanipulatedataandbuildpredictivemodels |