Mastering machine learning algorithms :: expert techniques to implement popular machine learning algorithms and fine-tune your models /
Annotation
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Annotation |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 9781788625906 1788625900 1788621115 9781788621113 |
Internformat
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBA-on1042342272 | ||
| 003 | OCoLC | ||
| 005 | 20241004212047.0 | ||
| 006 | m o d | ||
| 007 | cr unu|||||||| | ||
| 008 | 180702s2018 enka o 000 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d OCLCF |d TOH |d STF |d DEBBG |d TEFOD |d CEF |d CNCEN |d G3B |d S9I |d UAB |d AU@ |d VT2 |d C6I |d N$T |d UX1 |d K6U |d OCLCO |d OCLCQ |d OCLCO |d NZAUC |d OCLCQ |d PSYSI |d OCLCQ |d OCLCO |d OCLCL |d OCLCQ | ||
| 019 | |a 1175628394 | ||
| 020 | |a 9781788625906 |q (electronic bk.) | ||
| 020 | |a 1788625900 |q (electronic bk.) | ||
| 020 | |a 1788621115 | ||
| 020 | |a 9781788621113 | ||
| 024 | 3 | |a 9781788621113 | |
| 035 | |a (OCoLC)1042342272 |z (OCoLC)1175628394 | ||
| 037 | |a CL0500000976 |b Safari Books Online | ||
| 037 | |a 80479F1A-83BB-4D38-BFE3-7A91840FDC3D |b OverDrive, Inc. |n http://www.overdrive.com | ||
| 050 | 4 | |a Q325.5 | |
| 082 | 7 | |a 006.31 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Bonaccorso, Giuseppe, |e author. | |
| 245 | 1 | 0 | |a Mastering machine learning algorithms : |b expert techniques to implement popular machine learning algorithms and fine-tune your models / |c Giuseppe Bonaccorso. |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2018. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file | ||
| 588 | 0 | |a Online resource; title from title page (Safari, viewed June 29, 2018). | |
| 520 | 8 | |a Annotation |b Explore and master the most important algorithms for solving complex machine learning problems. Key FeaturesDiscover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and moreBook DescriptionMachine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learnExplore how a ML model can be trained, optimized, and evaluatedUnderstand how to create and learn static and dynamic probabilistic modelsSuccessfully cluster high-dimensional data and evaluate model accuracyDiscover how artificial neural networks work and how to train, optimize, and validate themWork with Autoencoders and Generative Adversarial NetworksApply label spreading and propagation to large datasetsExplore the most important Reinforcement Learning techniquesWho this book is forThis book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide. | |
| 650 | 0 | |a Machine learning. |0 http://id.loc.gov/authorities/subjects/sh85079324 | |
| 650 | 0 | |a Computer algorithms. |0 http://id.loc.gov/authorities/subjects/sh91000149 | |
| 650 | 2 | |a Algorithms |0 https://id.nlm.nih.gov/mesh/D000465 | |
| 650 | 2 | |a Machine Learning |0 https://id.nlm.nih.gov/mesh/D000069550 | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Algorithmes. | |
| 650 | 7 | |a algorithms. |2 aat | |
| 650 | 7 | |a Mathematical theory of computation. |2 bicssc | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc | |
| 650 | 7 | |a Machine learning. |2 bicssc | |
| 650 | 7 | |a Information architecture. |2 bicssc | |
| 650 | 7 | |a Database design & theory. |2 bicssc | |
| 650 | 7 | |a Computers |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Computers |x Machine Theory. |2 bisacsh | |
| 650 | 7 | |a Computers |x Data Modeling & Design. |2 bisacsh | |
| 650 | 7 | |a Computer algorithms |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 856 | 4 | 0 | |l FWS01 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1823677 |3 Volltext |
| 938 | |a EBSCOhost |b EBSC |n 1823677 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBA | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-on1042342272 |
|---|---|
| _version_ | 1816882464450150400 |
| adam_text | |
| any_adam_object | |
| author | Bonaccorso, Giuseppe |
| author_facet | Bonaccorso, Giuseppe |
| author_role | aut |
| author_sort | Bonaccorso, Giuseppe |
| author_variant | g b gb |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | Q325 |
| callnumber-raw | Q325.5 |
| callnumber-search | Q325.5 |
| callnumber-sort | Q 3325.5 |
| callnumber-subject | Q - General Science |
| collection | ZDB-4-EBA |
| ctrlnum | (OCoLC)1042342272 |
| dewey-full | 006.31 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.31 |
| dewey-search | 006.31 |
| dewey-sort | 16.31 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05104cam a2200613 i 4500</leader><controlfield tag="001">ZDB-4-EBA-on1042342272</controlfield><controlfield tag="003">OCoLC</controlfield><controlfield tag="005">20241004212047.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr unu||||||||</controlfield><controlfield tag="008">180702s2018 enka o 000 0 eng d</controlfield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">UMI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">UMI</subfield><subfield code="d">OCLCF</subfield><subfield code="d">TOH</subfield><subfield code="d">STF</subfield><subfield code="d">DEBBG</subfield><subfield code="d">TEFOD</subfield><subfield code="d">CEF</subfield><subfield code="d">CNCEN</subfield><subfield code="d">G3B</subfield><subfield code="d">S9I</subfield><subfield code="d">UAB</subfield><subfield code="d">AU@</subfield><subfield code="d">VT2</subfield><subfield code="d">C6I</subfield><subfield code="d">N$T</subfield><subfield code="d">UX1</subfield><subfield code="d">K6U</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">NZAUC</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">PSYSI</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCL</subfield><subfield code="d">OCLCQ</subfield></datafield><datafield tag="019" ind1=" " ind2=" "><subfield code="a">1175628394</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781788625906</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1788625900</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1788621115</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781788621113</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9781788621113</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1042342272</subfield><subfield code="z">(OCoLC)1175628394</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">CL0500000976</subfield><subfield code="b">Safari Books Online</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">80479F1A-83BB-4D38-BFE3-7A91840FDC3D</subfield><subfield code="b">OverDrive, Inc.</subfield><subfield code="n">http://www.overdrive.com</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">Q325.5</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">006.31</subfield><subfield code="2">23</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">MAIN</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Bonaccorso, Giuseppe,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mastering machine learning algorithms :</subfield><subfield code="b">expert techniques to implement popular machine learning algorithms and fine-tune your models /</subfield><subfield code="c">Giuseppe Bonaccorso.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK :</subfield><subfield code="b">Packt Publishing,</subfield><subfield code="c">2018.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (1 volume) :</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="347" ind1=" " ind2=" "><subfield code="a">data file</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Online resource; title from title page (Safari, viewed June 29, 2018).</subfield></datafield><datafield tag="520" ind1="8" ind2=" "><subfield code="a">Annotation</subfield><subfield code="b">Explore and master the most important algorithms for solving complex machine learning problems. Key FeaturesDiscover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and moreBook DescriptionMachine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learnExplore how a ML model can be trained, optimized, and evaluatedUnderstand how to create and learn static and dynamic probabilistic modelsSuccessfully cluster high-dimensional data and evaluate model accuracyDiscover how artificial neural networks work and how to train, optimize, and validate themWork with Autoencoders and Generative Adversarial NetworksApply label spreading and propagation to large datasetsExplore the most important Reinforcement Learning techniquesWho this book is forThis book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh85079324</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Computer algorithms.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh91000149</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Algorithms</subfield><subfield code="0">https://id.nlm.nih.gov/mesh/D000465</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Machine Learning</subfield><subfield code="0">https://id.nlm.nih.gov/mesh/D000069550</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Apprentissage automatique.</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Algorithmes.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">algorithms.</subfield><subfield code="2">aat</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Mathematical theory of computation.</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Artificial intelligence.</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning.</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Information architecture.</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Database design & theory.</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Computers</subfield><subfield code="x">Intelligence (AI) & Semantics.</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Computers</subfield><subfield code="x">Machine Theory.</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Computers</subfield><subfield code="x">Data Modeling & Design.</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Computer algorithms</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">fast</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">FWS01</subfield><subfield code="p">ZDB-4-EBA</subfield><subfield code="q">FWS_PDA_EBA</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1823677</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">1823677</subfield></datafield><datafield tag="994" ind1=" " ind2=" "><subfield code="a">92</subfield><subfield code="b">GEBAY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-EBA</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-4-EBA-on1042342272 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:29:02Z |
| institution | BVB |
| isbn | 9781788625906 1788625900 1788621115 9781788621113 |
| language | English |
| oclc_num | 1042342272 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (1 volume) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | Packt Publishing, |
| record_format | marc |
| spelling | Bonaccorso, Giuseppe, author. Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / Giuseppe Bonaccorso. Birmingham, UK : Packt Publishing, 2018. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file Online resource; title from title page (Safari, viewed June 29, 2018). Annotation Explore and master the most important algorithms for solving complex machine learning problems. Key FeaturesDiscover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and moreBook DescriptionMachine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learnExplore how a ML model can be trained, optimized, and evaluatedUnderstand how to create and learn static and dynamic probabilistic modelsSuccessfully cluster high-dimensional data and evaluate model accuracyDiscover how artificial neural networks work and how to train, optimize, and validate themWork with Autoencoders and Generative Adversarial NetworksApply label spreading and propagation to large datasetsExplore the most important Reinforcement Learning techniquesWho this book is forThis book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide. Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. algorithms. aat Mathematical theory of computation. bicssc Artificial intelligence. bicssc Machine learning. bicssc Information architecture. bicssc Database design & theory. bicssc Computers Intelligence (AI) & Semantics. bisacsh Computers Machine Theory. bisacsh Computers Data Modeling & Design. bisacsh Computer algorithms fast Machine learning fast FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1823677 Volltext |
| spellingShingle | Bonaccorso, Giuseppe Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. algorithms. aat Mathematical theory of computation. bicssc Artificial intelligence. bicssc Machine learning. bicssc Information architecture. bicssc Database design & theory. bicssc Computers Intelligence (AI) & Semantics. bisacsh Computers Machine Theory. bisacsh Computers Data Modeling & Design. bisacsh Computer algorithms fast Machine learning fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh91000149 https://id.nlm.nih.gov/mesh/D000465 https://id.nlm.nih.gov/mesh/D000069550 |
| title | Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / |
| title_auth | Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / |
| title_exact_search | Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / |
| title_full | Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / Giuseppe Bonaccorso. |
| title_fullStr | Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / Giuseppe Bonaccorso. |
| title_full_unstemmed | Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models / Giuseppe Bonaccorso. |
| title_short | Mastering machine learning algorithms : |
| title_sort | mastering machine learning algorithms expert techniques to implement popular machine learning algorithms and fine tune your models |
| title_sub | expert techniques to implement popular machine learning algorithms and fine-tune your models / |
| topic | Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. algorithms. aat Mathematical theory of computation. bicssc Artificial intelligence. bicssc Machine learning. bicssc Information architecture. bicssc Database design & theory. bicssc Computers Intelligence (AI) & Semantics. bisacsh Computers Machine Theory. bisacsh Computers Data Modeling & Design. bisacsh Computer algorithms fast Machine learning fast |
| topic_facet | Machine learning. Computer algorithms. Algorithms Machine Learning Apprentissage automatique. Algorithmes. algorithms. Mathematical theory of computation. Artificial intelligence. Information architecture. Database design & theory. Computers Intelligence (AI) & Semantics. Computers Machine Theory. Computers Data Modeling & Design. Computer algorithms Machine learning |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1823677 |
| work_keys_str_mv | AT bonaccorsogiuseppe masteringmachinelearningalgorithmsexperttechniquestoimplementpopularmachinelearningalgorithmsandfinetuneyourmodels |