Advanced Data Analytics Using Python, 2nd Edition
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Numerical Methods for Ordinary Differential Equations
In this book we discuss several numerical methods for solving ordinary differential equations. We emphasize the aspects that play an important role in practical problems. We con?ne ourselves to ordinary differential equations with the exception of the last chapter in which we discuss the heat equation, a parabolic partial differential equation. The techniques discussed in the intro-ductory chapters, for instance interpolation, numerical quadrature and the solution to nonlinear equations, may also be used outside the context of differential equations. They have been in-cluded to make the book self-contained as far as the numerical aspects are concerned. Chapters, sections and exercises marked with a * are not part of the Delft Institutional Package. The numerical examples in this book were implemented in Matlab, but also Python or any other programming language could be used. A list of references to background knowledge and related literature can be found at the end of this book. ...
In this book we discuss several numerical methods for solving ordinary differential equations. We emphasize the aspects that play an important role in practical problems. We con?ne ourselves to ordinary differential equations with the exception of the last chapter in which we discuss the heat equation, a parabolic partial differential equation. The techniques discussed in the intro-ductory chapters, for instance interpolation, numerical quadrature and the solution to nonlinear equations, may also be used outside the context of differential equations. They have been in-cluded to make the book self-contained as far as the numerical aspects are concerned. Chapters, sections and exercises marked with a * are not part of the Delft Institutional Package. The numerical examples in this book were implemented in Matlab, but also Python or any other programming language could be used. A list of references to background knowledge and related literature can be found at the end of this book. ...
Spring 6 Recipes, 5th Edition
This in-depth Spring-based Java developer code reference has been updated and now solves many of your Spring Framework 6 problems using reusable, complete and real-world working code examples. Spring 6 Recipes (5th Edition) now includes Spring Native which speeds up your Java-based Spring Framework built enterprise, native cloud, web applications and microservices. It also has been updated to now include Spring R2DBC for Reactive Relational Database Connectivity, a specification to integrate SQL databases, like PostgreSQL, MySQL and more, using reactive drivers. Furthermore, this book includes additional coverage of WebFlux for more reactive Spring web applications. Reactive programming allows you to build systems that are resilient to high load, especially common in the more complex enterprise, native cloud applications that Spring Framework lets you build. This updated edition also uses code snippets and examples based on newest available standard long term support release of Java ...
This in-depth Spring-based Java developer code reference has been updated and now solves many of your Spring Framework 6 problems using reusable, complete and real-world working code examples. Spring 6 Recipes (5th Edition) now includes Spring Native which speeds up your Java-based Spring Framework built enterprise, native cloud, web applications and microservices. It also has been updated to now include Spring R2DBC for Reactive Relational Database Connectivity, a specification to integrate SQL databases, like PostgreSQL, MySQL and more, using reactive drivers. Furthermore, this book includes additional coverage of WebFlux for more reactive Spring web applications. Reactive programming allows you to build systems that are resilient to high load, especially common in the more complex enterprise, native cloud applications that Spring Framework lets you build. This updated edition also uses code snippets and examples based on newest available standard long term support release of Java ...