Alexandre Bergel – författare

Cover classical algorithms commonly used as artificial intelligence techniques and program agile artificial intelligence applications using Pharo. This book takes a practical approach by presenting the implementation details to illustrate the numerous concepts it explains. Along the way, you’ll learn neural net fundamentals to set you up for practical examples such as the traveling salesman problem and cover genetic algorithms including a fun zoomorphic creature example. Furthermore, Practical Agile AI with Pharo finishes with a data classification application and two game applications including a Pong-like game and a Flappy Bird-like game. This book is informative and fun, giving you source code to play along with. You’ll be able to take this source code and apply it to your own projects.  What You Will LearnUse neurons, neural networks, learning theory, and moreWork with genetic algorithms Incorporate neural network principles when working towards neuroevolution Include neural network fundamentals when building three Pharo-based applicationsWho This Book Is ForCoders and data scientists who are experienced programmers and have at least some prior experience with AI or deep learning. They may be new to Pharo programming, but some prior experience with it would be helpful.

Cover classical algorithms commonly used as artificial intelligence techniques and program agile artificial intelligence applications using Pharo. This book takes a practical approach by presenting the implementation details to illustrate the numerous concepts it explains. Along the way, you’ll learn neural net fundamentals to set you up for practical examples such as the traveling salesman problem and cover genetic algorithms including a fun zoomorphic creature example. Furthermore, Practical Agile AI with Pharo finishes with a data classification application and two game applications including a Pong-like game and a Flappy Bird-like game. This book is informative and fun, giving you source code to play along with. You’ll be able to take this source code and apply it to your own projects.  What You Will LearnUse neurons, neural networks, learning theory, and moreWork with genetic algorithms Incorporate neural network principles when working towards neuroevolution Include neural network fundamentals when building three Pharo-based applicationsWho This Book Is ForCoders and data scientists who are experienced programmers and have at least some prior experience with AI or deep learning. They may be new to Pharo programming, but some prior experience with it would be helpful. 

Use the Pharo interactive development environment to significantly reduce the cost of creating interactive visualizations. This book shows how Pharo leverages visualization development against traditional frameworks and toolkits.Agile Visualization with Pharo focuses on the Roassal visualization engine and first presents the basic and necessary tools to visualize data, including an introduction to the Pharo programming language. Once you’ve grasped the basics, you’ll learn all about the development environment offered by Roassal. The book provides numerous ready-to-use examples. You’ll work on several applications, including visualizing the training phase of reinforcement learning (a powerful machine learning algorithm) and generating software visualizations from GitHub. This book covers aspects that are relevant for engineers and academics to successfully design and implement interactive visualizations.What You Will LearnImplement agile data visualization using the Pharo programming languageChart, plot, and curve using GrapherBuild and draw graphs using MondrianImplement reinforcement learning (Q-Learning, from scratch) and use visualizations to monitor learning and state explorationUse GitHub Action to generate software visualizations (UML class diagram, test coverage) at each commit Who This Book Is ForProgrammers with some prior exposure to data visualization and computer vision who may be new to the Pharo programming language. This book is also for those with some Pharo experience looking to apply it to data visualization.

Use the Pharo interactive development environment to significantly reduce the cost of creating interactive visualizations. This book shows how Pharo leverages visualization development against traditional frameworks and toolkits.

Agile Visualization with Pharo focuses on the Roassal visualization engine and first presents the basic and necessary tools to visualize data, including an introduction to the Pharo programming language. Once you’ve grasped the basics, you’ll learn all about the development environment offered by Roassal. The book provides numerous ready-to-use examples. You’ll work on several applications, including visualizing the training phase of reinforcement learning (a powerful machine learning algorithm) and generating software visualizations from GitHub.

This book covers aspects that are relevant for engineers and academics to successfully design and implement interactive visualizations.

What You Will Learn

Implement agile data visualization using the Pharo programming languageChart, plot, and curve using GrapherBuild and draw graphs using MondrianImplement reinforcement learning (Q-Learning, from scratch) and use visualizations to monitor learning and state explorationUse GitHub Action to generate software visualizations (UML class diagram, test coverage) at each commit 

Who This Book Is For

Programmers with some prior exposure to data visualization and computer vision who may be new to the Pharo programming language. This book is also for those with some Pharo experience looking to apply it to data visualization. 

This book constitutes the refereed proceedings of the 8th International Symposium on Software Composition, SC 2009, held in Zurich, Switzerland, in July 2009. The workshop has been organized as an event co-located with the TOOLS Europe 2009 conference. The 10 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 34 submissions. The papers reflect current research in software composition to foster developing of composition models and techniques by using aspect- and service-oriented programming, specification of component contracts and protocols, methods of correct components composition, as well as verification, validation and testing techniques - even in pervasive computing environments and for the Web.

This book constitutes the refereed proceedings of the 8th International Symposium on Software Composition, SC 2009, held in Zurich, Switzerland, in July 2009. The workshop has been organized as an event co-located with the TOOLS Europe 2009 conference. The 10 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 34 submissions. The papers reflect current research in software composition to foster developing of composition models and techniques by using aspect- and service-oriented programming, specification of component contracts and protocols, methods of correct components composition, as well as verification, validation and testing techniques - even in pervasive computing environments and for the Web.

Develop a thorough grasp of artificial intelligence through practical implementations in Julia. This trailblazing book covers classical AI algorithms and provides practical implementations of agile AI applications, highlighting Julia's versatility and high-performance capabilities for AI development.This book takes a practical approach to ensure that readers translate theoretical concepts into tangible, real-world scenarios. Along the way, you will learn and implement neural networks, genetic algorithms, and neuroevolution from scratch. Author Dr. Alexandre Bergel uses practical examples, such as solutions to the traveling sales problem and a fun platform game (including a random level generator) to reinforce AI techniques. It also introduces Darwinian evolution principles, demonstrating how to evolve zoomorphic organisms to solve particular tasks, such as stair climbing or going over obstacles.This book stands out as among the earliest to delve into Genertic Algorithms and Neuroevolutions in Julia, and it is one of the few available that offers a comprehensive implementation of Neuroevolution. It is equally as fun as it is informative, providing readers with source code to play along with and apply to future projects. What You Will Learn: Solve simple classification tasks using neural networksUse genetic algorithms to solve complex algorithmic problemsApply Darwinian evolution principles to evolve artificially living creaturesDiscover how to Neuroevolution to build an artificial player to solve a platform game Who This Book is For: This book is written for software engineers, programmers and developers who are eager to gain practical insights into AI implementation using Julia at a beginner/intermediate level