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B 76
Bonaccorso, Giuseppe.
Machine Learning Algorithms : : Popular Algorithms for Data Science and Machine Learning, 2nd Edition. / Giuseppe. Bonaccorso. - 2nd ed. - Birmingham : : Packt Publishing Ltd,, 2018. - 1 online resource (514 pages). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/D9D16600-8F9C-45A4-B8EC-B980EF369FE7. - ISBN 9781789345483. - ISBN 1789345480
Introducing semi-supervised Support Vector Machines (S3VM). Print version record.
Параллельные издания: Print version: : Bonaccorso, Giuseppe. Machine Learning Algorithms : Popular Algorithms for Data Science and Machine Learning, 2nd Edition. - Birmingham : Packt Publishing Ltd, ©2018. - ISBN 9781789347999
Содержание:
Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: A Gentle Introduction to Machine Learning; Introduction -- classic and adaptive machines; Descriptive analysis; Predictive analysis; Only learning matters; Supervised learning; Unsupervised learning; Semi-supervised learning; Reinforcement learning; Computational neuroscience; Beyond machine learning -- deep learning and bio-inspired adaptive systems; Machine learning and big data; Summary; Chapter 2: Important Elements in Machine Learning; Data formats; Multiclass strategies.
One-vs-allOne-vs-one; Learnability; Underfitting and overfitting; Error measures and cost functions; PAC learning; Introduction to statistical learning concepts; MAP learning; Maximum likelihood learning; Class balancing; Resampling with replacement; SMOTE resampling; Elements of information theory; Entropy; Cross-entropy and mutual information ; Divergence measures between two probability distributions; Summary; Chapter 3: Feature Selection and Feature Engineering; scikit-learn toy datasets; Creating training and test sets; Managing categorical data; Managing missing features.
Data scaling and normalizationWhitening; Feature selection and filtering; Principal Component Analysis; Non-Negative Matrix Factorization; Sparse PCA; Kernel PCA; Independent Component Analysis; Atom extraction and dictionary learning; Visualizing high-dimensional datasets using t-SNE; Summary; Chapter 4: Regression Algorithms; Linear models for regression; A bidimensional example; Linear regression with scikit-learn and higher dimensionality; R2 score; Explained variance; Regressor analytic expression; Ridge, Lasso, and ElasticNet; Ridge; Lasso; ElasticNet; Robust regression; RANSAC.
Huber regressionBayesian regression; Polynomial regression; Isotonic regression; Summary; Chapter 5: Linear Classification Algorithms; Linear classification; Logistic regression; Implementation and optimizations; Stochastic gradient descent algorithms; Passive-aggressive algorithms; Passive-aggressive regression; Finding the optimal hyperparameters through a grid search; Classification metrics; Confusion matrix; Precision; Recall; F-Beta; Cohen's Kappa; Global classification report; Learning curve; ROC curve; Summary; Chapter 6: Naive Bayes and Discriminant Analysis; Bayes' theorem.
~РУБ DDC 006.31
Рубрики: Computers--Intelligence (AI) & Semantics.
Computers--Data Modeling & Design.
Database design & theory.
Artificial intelligence.
Machine learning.
Information architecture.
Computers--Machine Theory.
Mathematical theory of computation.
Machine learning.
Computer algorithms.
Computer algorithms.
Machine learning.
Аннотация: Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. This book will act as an entry point for anyone who wants to make a career in Machine Learning. It covers algorithms like Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, and Feature engineering.
B 76
Bonaccorso, Giuseppe.
Machine Learning Algorithms : : Popular Algorithms for Data Science and Machine Learning, 2nd Edition. / Giuseppe. Bonaccorso. - 2nd ed. - Birmingham : : Packt Publishing Ltd,, 2018. - 1 online resource (514 pages). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/D9D16600-8F9C-45A4-B8EC-B980EF369FE7. - ISBN 9781789345483. - ISBN 1789345480
Introducing semi-supervised Support Vector Machines (S3VM). Print version record.
Параллельные издания: Print version: : Bonaccorso, Giuseppe. Machine Learning Algorithms : Popular Algorithms for Data Science and Machine Learning, 2nd Edition. - Birmingham : Packt Publishing Ltd, ©2018. - ISBN 9781789347999
Содержание:
Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: A Gentle Introduction to Machine Learning; Introduction -- classic and adaptive machines; Descriptive analysis; Predictive analysis; Only learning matters; Supervised learning; Unsupervised learning; Semi-supervised learning; Reinforcement learning; Computational neuroscience; Beyond machine learning -- deep learning and bio-inspired adaptive systems; Machine learning and big data; Summary; Chapter 2: Important Elements in Machine Learning; Data formats; Multiclass strategies.
One-vs-allOne-vs-one; Learnability; Underfitting and overfitting; Error measures and cost functions; PAC learning; Introduction to statistical learning concepts; MAP learning; Maximum likelihood learning; Class balancing; Resampling with replacement; SMOTE resampling; Elements of information theory; Entropy; Cross-entropy and mutual information ; Divergence measures between two probability distributions; Summary; Chapter 3: Feature Selection and Feature Engineering; scikit-learn toy datasets; Creating training and test sets; Managing categorical data; Managing missing features.
Data scaling and normalizationWhitening; Feature selection and filtering; Principal Component Analysis; Non-Negative Matrix Factorization; Sparse PCA; Kernel PCA; Independent Component Analysis; Atom extraction and dictionary learning; Visualizing high-dimensional datasets using t-SNE; Summary; Chapter 4: Regression Algorithms; Linear models for regression; A bidimensional example; Linear regression with scikit-learn and higher dimensionality; R2 score; Explained variance; Regressor analytic expression; Ridge, Lasso, and ElasticNet; Ridge; Lasso; ElasticNet; Robust regression; RANSAC.
Huber regressionBayesian regression; Polynomial regression; Isotonic regression; Summary; Chapter 5: Linear Classification Algorithms; Linear classification; Logistic regression; Implementation and optimizations; Stochastic gradient descent algorithms; Passive-aggressive algorithms; Passive-aggressive regression; Finding the optimal hyperparameters through a grid search; Classification metrics; Confusion matrix; Precision; Recall; F-Beta; Cohen's Kappa; Global classification report; Learning curve; ROC curve; Summary; Chapter 6: Naive Bayes and Discriminant Analysis; Bayes' theorem.
Рубрики: Computers--Intelligence (AI) & Semantics.
Computers--Data Modeling & Design.
Database design & theory.
Artificial intelligence.
Machine learning.
Information architecture.
Computers--Machine Theory.
Mathematical theory of computation.
Machine learning.
Computer algorithms.
Computer algorithms.
Machine learning.
Аннотация: Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. This book will act as an entry point for anyone who wants to make a career in Machine Learning. It covers algorithms like Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, and Feature engineering.
2.
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K 83
Krishnakumar, Arunkumar,.
Quantum computing and Blockchain in business : : exploring the applications, challenges, and collision of quantum computing and blockchain / / Arunkumar Krishnakumar. - Birmingham, UK : : Packt Publishing,, 2020. - 1 online resource (1 volume) : : il. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/58D30AF0-02FA-4E32-9F42-E5F6D4682ECC. - ISBN 1838646132. - ISBN 9781838646134 (electronic bk.)
Description based on online resource; title from title page (Safari, viewed September 3, 2020).
Содержание:
Table of ContentsIntroduction to Quantum Computing and BlockchainQuantum Computing - Key Discussion PointsThe Data EconomyThe Impact on Financial ServicesInterview with Dr. Dave Snelling, Fujitsu FellowThe Impact on Healthcare and PharmaInterview with Dr. B. Rajathilagam, Head of AI Research, Amrita Vishwa VidyapeethamThe Impact on GovernanceInterview with Max Henderson, Senior Data Scientist, Rigetti and QxBranchThe Impact on Smart Cities and EnvironmentInterview with Sam McArdle, Quantum Computing Researcher at the University of OxfordThe Impact on ChemistryThe Impact on Logistics(N.B. Please use the Look Inside option to see further chapters).
~РУБ DDC 658.514
Рубрики: Quantum computing.
Blockchains (Databases)
Information technology--Management.
Technological innovations--Management.
Coding theory & cryptology.
Data encryption.
Artificial intelligence.
Machine learning.
Mathematical theory of computation.
Computers--Intelligence (AI) & Semantics.
Computers--Security--Cryptography.
Computers--Machine Theory.
Blockchains (Databases)
Information technology--Management
Quantum computing
Technological innovations--Management
K 83
Krishnakumar, Arunkumar,.
Quantum computing and Blockchain in business : : exploring the applications, challenges, and collision of quantum computing and blockchain / / Arunkumar Krishnakumar. - Birmingham, UK : : Packt Publishing,, 2020. - 1 online resource (1 volume) : : il. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/58D30AF0-02FA-4E32-9F42-E5F6D4682ECC. - ISBN 1838646132. - ISBN 9781838646134 (electronic bk.)
Description based on online resource; title from title page (Safari, viewed September 3, 2020).
Содержание:
Table of ContentsIntroduction to Quantum Computing and BlockchainQuantum Computing - Key Discussion PointsThe Data EconomyThe Impact on Financial ServicesInterview with Dr. Dave Snelling, Fujitsu FellowThe Impact on Healthcare and PharmaInterview with Dr. B. Rajathilagam, Head of AI Research, Amrita Vishwa VidyapeethamThe Impact on GovernanceInterview with Max Henderson, Senior Data Scientist, Rigetti and QxBranchThe Impact on Smart Cities and EnvironmentInterview with Sam McArdle, Quantum Computing Researcher at the University of OxfordThe Impact on ChemistryThe Impact on Logistics(N.B. Please use the Look Inside option to see further chapters).
Рубрики: Quantum computing.
Blockchains (Databases)
Information technology--Management.
Technological innovations--Management.
Coding theory & cryptology.
Data encryption.
Artificial intelligence.
Machine learning.
Mathematical theory of computation.
Computers--Intelligence (AI) & Semantics.
Computers--Security--Cryptography.
Computers--Machine Theory.
Blockchains (Databases)
Information technology--Management
Quantum computing
Technological innovations--Management
3.
Подробнее
C 73
Communicating user experience : : applying local strategies research to digital media design / / edited by Trudy Milburn. - Lanham : : Lexington Books,, [2015]. - 1 online resource (xxiv, 224 pages). : il. - (Studies in new media). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/2730D91E-3C36-47CD-BFBF-527044A70163. - ISBN 9781498506144 (ebook). - ISBN 1498506143
Description based on print version record and CIP data provided by publisher; resource not viewed.
Параллельные издания: Print version: : Communicating user experience. - Lanham : Lexington Books, [2015]. - ISBN 9781498506137 (cloth : alk. paper)
~РУБ DDC 004.01/9
Рубрики: Human-computer interaction.
Digital media.
COMPUTERS--Computer Literacy.
COMPUTERS--Computer Science.
COMPUTERS--Data Processing.
COMPUTERS--Hardware--General.
COMPUTERS--Information Technology.
COMPUTERS--Machine Theory.
COMPUTERS--Reference.
Digital media.
Human-computer interaction.
Доп.точки доступа:
Milburn, Trudy, \editor.\
C 73
Communicating user experience : : applying local strategies research to digital media design / / edited by Trudy Milburn. - Lanham : : Lexington Books,, [2015]. - 1 online resource (xxiv, 224 pages). : il. - (Studies in new media). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/2730D91E-3C36-47CD-BFBF-527044A70163. - ISBN 9781498506144 (ebook). - ISBN 1498506143
Description based on print version record and CIP data provided by publisher; resource not viewed.
Параллельные издания: Print version: : Communicating user experience. - Lanham : Lexington Books, [2015]. - ISBN 9781498506137 (cloth : alk. paper)
Рубрики: Human-computer interaction.
Digital media.
COMPUTERS--Computer Literacy.
COMPUTERS--Computer Science.
COMPUTERS--Data Processing.
COMPUTERS--Hardware--General.
COMPUTERS--Information Technology.
COMPUTERS--Machine Theory.
COMPUTERS--Reference.
Digital media.
Human-computer interaction.
Доп.точки доступа:
Milburn, Trudy, \editor.\
4.
Подробнее
S 73
Sosnovshchenko, Alexander,.
Machine learning with Swift : : artificial intelligence for iOS / / Alexander Sosnovshchenko. - Birmingham, UK : : Packt Publishing,, 2018. - 1 online resource (1 volume) : : il. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/337B8A1F-7601-44C6-8A3D-247D0CE099E1. - ISBN 9781787123526 (electronic bk.). - ISBN 1787123529 (electronic bk.). - ISBN 1787121518. - ISBN 9781787121515
Online resource; title from title page (Safari, viewed March 20, 2018).
~РУБ DDC 004.1675
Рубрики: Swift (Computer program language)
Machine learning.
Artificial intelligence.
Application software--Development.
Artificial Intelligence
Swift (Langage de programmation)
Apprentissage automatique.
Intelligence artificielle.
Logiciels d'application--Développement.
artificial intelligence.
Macintosh OS.
Neural networks & fuzzy systems.
Artificial intelligence.
Computers--Neural Networks.
Computers--Operating Systems--Macintosh.
Computers--Intelligence (AI) & Semantics.
COMPUTERS--Computer Literacy.
COMPUTERS--Computer Science.
COMPUTERS--Data Processing.
COMPUTERS--Hardware--General.
COMPUTERS--Information Technology.
COMPUTERS--Machine Theory.
COMPUTERS--Reference.
Application software--Development.
Artificial intelligence.
Machine learning.
Swift (Computer program language)
S 73
Sosnovshchenko, Alexander,.
Machine learning with Swift : : artificial intelligence for iOS / / Alexander Sosnovshchenko. - Birmingham, UK : : Packt Publishing,, 2018. - 1 online resource (1 volume) : : il. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/337B8A1F-7601-44C6-8A3D-247D0CE099E1. - ISBN 9781787123526 (electronic bk.). - ISBN 1787123529 (electronic bk.). - ISBN 1787121518. - ISBN 9781787121515
Online resource; title from title page (Safari, viewed March 20, 2018).
Рубрики: Swift (Computer program language)
Machine learning.
Artificial intelligence.
Application software--Development.
Artificial Intelligence
Swift (Langage de programmation)
Apprentissage automatique.
Intelligence artificielle.
Logiciels d'application--Développement.
artificial intelligence.
Macintosh OS.
Neural networks & fuzzy systems.
Artificial intelligence.
Computers--Neural Networks.
Computers--Operating Systems--Macintosh.
Computers--Intelligence (AI) & Semantics.
COMPUTERS--Computer Literacy.
COMPUTERS--Computer Science.
COMPUTERS--Data Processing.
COMPUTERS--Hardware--General.
COMPUTERS--Information Technology.
COMPUTERS--Machine Theory.
COMPUTERS--Reference.
Application software--Development.
Artificial intelligence.
Machine learning.
Swift (Computer program language)
5.
Подробнее
K 27
Kedia, Aman,.
Hands-on Python natural language processing : : explore tools and techniques to analyze and process text with a view to building real-world NLP applications / / Aman Kedia, Mayank Rasu. - Birmingham, UK : : Packt Publishing,, 2020. - 1 online resource (1 volume) : : il. - Includes bibliographical references. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/334CF680-946D-499A-90C9-44D55E5E64A3. - ISBN 1838982582. - ISBN 9781838982584 (electronic bk.)
Description based on online resource; title from title page (Safari, viewed October 27, 2020).
~РУБ DDC 006.3/5
Рубрики: Natural language processing (Computer science)
Python (Computer program language)
Mathematical theory of computation.
Natural language & machine translation.
Machine learning.
Data capture & analysis.
Computers--Machine Theory.
Computers--Natural Language Processing.
Computers--Data Processing.
Доп.точки доступа:
Rasu, Mayank, \author.\
K 27
Kedia, Aman,.
Hands-on Python natural language processing : : explore tools and techniques to analyze and process text with a view to building real-world NLP applications / / Aman Kedia, Mayank Rasu. - Birmingham, UK : : Packt Publishing,, 2020. - 1 online resource (1 volume) : : il. - Includes bibliographical references. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/334CF680-946D-499A-90C9-44D55E5E64A3. - ISBN 1838982582. - ISBN 9781838982584 (electronic bk.)
Description based on online resource; title from title page (Safari, viewed October 27, 2020).
Рубрики: Natural language processing (Computer science)
Python (Computer program language)
Mathematical theory of computation.
Natural language & machine translation.
Machine learning.
Data capture & analysis.
Computers--Machine Theory.
Computers--Natural Language Processing.
Computers--Data Processing.
Доп.точки доступа:
Rasu, Mayank, \author.\
6.
Подробнее
M 35
Martinez, Jesus.
TensorFlow 2. 0 Computer Vision Cookbook [[electronic resource] :] : Implement Machine Learning Solutions to Overcome Various Computer Vision Challenges. / Jesus. Martinez. - Birmingham : : Packt Publishing, Limited,, 2021. - 1 online resource (542 p.). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/3B12102B-E8B5-472A-9881-525304350574. - ISBN 183882068X. - ISBN 9781838820688 (electronic bk.)
Description based upon print version of record.
Параллельные издания: Print version: : Martinez, Jesus TensorFlow 2. 0 Computer Vision Cookbook. - Birmingham : Packt Publishing, Limited,c2021
~РУБ DDC 006.31
Рубрики: COMPUTERS--Computer Vision & Pattern Recognition.
COMPUTERS--Image Processing.
COMPUTERS--Machine Theory.
Computer vision.
Machine learning.
Image processing--Digital techniques.
M 35
Martinez, Jesus.
TensorFlow 2. 0 Computer Vision Cookbook [[electronic resource] :] : Implement Machine Learning Solutions to Overcome Various Computer Vision Challenges. / Jesus. Martinez. - Birmingham : : Packt Publishing, Limited,, 2021. - 1 online resource (542 p.). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/3B12102B-E8B5-472A-9881-525304350574. - ISBN 183882068X. - ISBN 9781838820688 (electronic bk.)
Description based upon print version of record.
Параллельные издания: Print version: : Martinez, Jesus TensorFlow 2. 0 Computer Vision Cookbook. - Birmingham : Packt Publishing, Limited,c2021
Рубрики: COMPUTERS--Computer Vision & Pattern Recognition.
COMPUTERS--Image Processing.
COMPUTERS--Machine Theory.
Computer vision.
Machine learning.
Image processing--Digital techniques.
Page 1, Results: 6