Электронный каталог

DDC 006.3/5
R 33
Reese, Richard Martin, (1953-).
    Natural language processing with Java : : techniques for building machine learning and neural network models for NLP / / Richard M. Reese, AshishSingh Bhatia. - Second edition. - Birmingham, UK : : Packt Publishing,, 2018. - 1 online resource (1 volume) : : il. - (Community experience distilled). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/208C26CA-E05E-4508-9CD4-84D44FC266D9. - ISBN 9781788993067 (electronic bk.). - ISBN 1788993063 (electronic bk.)
Description based on online resource; title from title page (Safari, viewed August 27, 2018).

Reese, Richard Martin,. Natural language processing with Java : [Электронный ресурс] : techniques for building machine learning and neural network models for NLP / / Richard M. Reese, AshishSingh Bhatia., 2018. - 1 online resource (1 volume) : с.

DDC 006.3
P 32
Patel, Devangini.
    Hands-On Artificial Intelligence for Search [[electronic resource] :] : Building Intelligent Applications and Perform Enterprise Searches / / Devangini Patel. - Birmingham : : Packt Publishing Ltd,, 2018. - 1 online resource (120 p.). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/ABCEFB67-26EB-4797-8980-A5C5FE771AAD. - ISBN 9781789612479 (electronic bk.). - ISBN 1789612470 (electronic bk.)
Description based upon print version of record.
Параллельные издания: Print version: : Patel, Devangini Hands-On Artificial Intelligence for Search : Building Intelligent Applications and Perform Enterprise Searches. - Birmingham : Packt Publishing Ltd,c2018. - ISBN 9781789611151
    Содержание:
Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Understanding the Depth-First Search Algorithm; Installing and setting up libraries; Setting up Python; Setting up Graphviz; Installing pip; Introduction to file searching applications; Basic search concepts; Formulating the search problem; Building trees with nodes; Stack data structure; The DFS algorithm; Recursive DFS; Do it yourself; Summary; Chapter 2: Understanding the Breadth-First Search Algorithm; Understanding the LinkedIn connection feature; Graph data structure
Queue data structureThe BFS algorithm; BFS versus DFS; Order of traversal; Data structures; Memory; Optimal solution; Do it yourself; Summary; Chapter 3: Understanding the Heuristic Search Algorithm; Revisiting the navigation application; The priority queue data structure; Visualizing a search tree; Greedy BFS; A* Search; What is a good heuristic function? ; Properties of a good heuristic function; Admissible; Consistent; Summary; Other Books You May Enjoy; Index

Patel, Devangini. Hands-On Artificial Intelligence for Search [[electronic resource] :] : Building Intelligent Applications and Perform Enterprise Searches / / Devangini Patel., 2018. - 1 online resource (120 p.) с. (Введено оглавление)

DDC 006.2/2
E 45
Elk, Klaus,.
    Embedded software for the IoT / / Klaus Elk. - Third edition. - Boston : : Walter de Gruyter Inc.,, ©2019. - 1 online resource. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/EF5823A2-6435-4F3C-A534-5A11017D8DC1. - ISBN 9781547401024 (electronic bk.). - ISBN 1547401028 (electronic bk.). - ISBN 9781547401048 (electronic bk.). - ISBN 1547401044 (electronic bk.)
Online resource; title from PDF title page (EBSCO, viewed March 29, 2019)

Elk, Klaus,. Embedded software for the IoT / [Электронный ресурс] / Klaus Elk., ©2019. - 1 online resource с.

DDC 006.3/32
O-61

    Ontology makes sense [[electronic resource] :] : essays in honor of Nicola Guarino / / edited by Stefano Borgo, Roberta Ferrario, Claudio Masolo and Laure Vieu. - Amsterdam : : IOS Press,, 2019. - 1 online resource. - (Frontiers in artificial intelligence and applications ; ; v. 316). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/E55CB7E0-0FE5-4AB4-82C2-CDA70E0554A2. - ISBN 9781614999553 (electronic bk.). - ISBN 1614999554 (electronic bk.)
Includes index. Online resource; title from PDF title page (EBSCO, viewed May 21, 2019)

Ontology makes sense [[electronic resource] :] : essays in honor of Nicola Guarino / / edited by Stefano Borgo, Roberta Ferrario, Claudio Masolo and Laure Vieu., 2019. - 1 online resource с.

DDC 006.31
M 55
Mengle, Saket S. R.,
    Mastering machine learning on AWS : : advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow / / Saket S.R. Mengle, Maximo Gurmendez. - Birmingham, UK : : Packt Publishing, Limited,, 2019. - 1 online resource (293 pages). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/E64DB41C-5FE0-49C0-858F-11551992A3ED. - ISBN 1789347505 (ebook). - ISBN 9781789347500 (electronic bk.)
Description based on print version record.
Параллельные издания: Print version: : Mengle, Saket S. R. Mastering machine learning on AWS : advanced machine learning in Python Using SageMaker, Apache Spark, and TensorFlow. - Birmingham : Packt Publishing, Limited, ©2019. - ISBN 9781789349795
    Содержание:
Cover; Title Page; Copyright and Credits; Dedication; About Packt; Contributors; Table of Contents; Preface; Section 1: Machine Learning on AWS; Chapter 1: Getting Started with Machine Learning for AWS; How AWS empowers data scientists; Using AWS tools for machine learning; Identifying candidate problems that can be solved using machine learning; Machine learning project life cycle; Data gathering; Evaluation metrics; Algorithm selection; Deploying models; Summary; Exercise; Section 2: Implementing Machine Learning Algorithms at Scale on AWS
Chapter 2: Classifying Twitter Feeds with Naive BayesClassification algorithms; Feature types; Nominal features; Ordinal features; Continuous features; Naive Bayes classifier; Bayes' theorem; Posterior; Likelihood; Prior probability; Evidence; How the Naive Bayes algorithm works; Classifying text with language models; Collecting the tweets; Preparing the data; Building a Naive Bayes model through SageMaker notebooks; Naïve Bayes model on SageMaker notebooks using Apache Spark; Using SageMaker's BlazingText built-in ML service; Naive Bayes - pros and cons; Summary; Exercises
Chapter 3: Predicting House Value with Regression AlgorithmsPredicting the price of houses; Understanding linear regression; Linear least squares estimation; Maximum likelihood estimation; Gradient descent; Evaluating regression models; Mean absolute error; Mean squared error; Root mean squared error; R-squared; Implementing linear regression through scikit-learn; Implementing linear regression through Apache Spark; Implementing linear regression through SageMaker's linear Learner; Understanding logistic regression; Logistic regression in Spark; Pros and cons of linear models; Summary
Chapter 4: Predicting User Behavior with Tree-Based MethodsUnderstanding decision trees; Recursive splitting; Types of decision trees; Cost functions; Gini Impurity; Information gain; Criteria to stop splitting trees; Understanding random forest algorithms; Understanding gradient boosting algorithms; Predicting clicks on log streams; Introduction to Elastic Map Reduce (EMR); Training with Apache Spark on EMR; Getting the data; Preparing the data; Categorical encoding; One-hot encoding; Training a model; Evaluating our model; Area Under ROC Curve; Area under the precision-recall curve; Training tree ensembles on EMR Training gradient-boosted trees with the SageMaker services; Preparing the data; Training with SageMaker XGBoost; Applying and evaluating the model; Summary; Exercises
Chapter 5: Customer Segmentation Using Clustering Algorithms; Understanding How Clustering Algorithms Work; k-means clustering; Euclidean distance; Manhattan distance; Hierarchical clustering; Agglomerative clustering; Divisive clustering; Clustering with Apache Spark on EMR; Clustering with Spark and SageMaker on EMR; Understanding the purpose of the IAM role; Summary; Exercises; Chapter 6: Analyzing Visitor Patterns to Make Recommendations

Mengle, Saket S. R., Mastering machine learning on AWS : [Электронный ресурс] : advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow / / Saket S.R. Mengle, Maximo Gurmendez., 2019. - 1 online resource (293 pages) с. (Введено оглавление)