This book constitutes the refereed proceedings of the 13th International Conference on Algorithms and Complexity, CIAC 2023, which took place in Larnaca, Cyprus, during June 13-16, 2023.
This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023.
This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023.
This book constitutes the refereed proceedings of the 13th International Conference on Algorithms and Complexity, CIAC 2023, which took place in Larnaca, Cyprus, during June 13-16, 2023.
This textbook integrates scientific programming with the use of R and uses it both as a tool for applied problems and to aid in learning calculus ideas.
The Digital Twin book is about harnessing the power of technology, business practices, and the digital infrastructure to make revolutionary improvements for the benefit of society.
This book presents a short introduction to the main tools of optimization methodology including linear programming, steepest descent, conjugate gradients, and the Karush-Kuhn-Tucker-John conditions.
This dynamic reference work provides solutions to vital algorithmic problems for scholars, researchers, practitioners, teachers and students in fields such as computer science, mathematics, statistics, biology, economics, financial software, and medical informatics.
Absolute Essentials of Ethereum is a concise textbook which guides the reader through the fascinating world of the emerging Ethereum ecosystem, from the basics of how its blockchain works to cutting-edge applications.
Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlowKey FeaturesGet to grips with the different reinforcement and DRL algorithms for game developmentLearn how to implement components such as artificial agents, map and level generation, and audio generationGain insights into cutting-edge RL research and understand how it is similar to artificial general researchBook DescriptionWith the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects.
Apply neural network architectures to build state-of-the-art computer vision applications using the Python programming languageKey FeaturesGain a fundamental understanding of advanced computer vision and neural network models in use todayCover tasks such as low-level vision, image classification, and object detectionDevelop deep learning models on cloud platforms and optimize them using TensorFlow Lite and the OpenVINO toolkitBook DescriptionComputer vision allows machines to gain human-level understanding to visualize, process, and analyze images and videos.
Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network modelsKey FeaturesImplement GAN architectures to generate images, text, audio, 3D models, and moreUnderstand how GANs work and become an active contributor in the open source communityLearn how to generate photo-realistic images based on text descriptionsBook DescriptionWith continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning.
Fintech veteran and venture capitalist, Arunkumar Krishnakumar, cuts through the hype to bring us a first-hand look into how quantum computing and Blockchain together could redefine industries and life as we know it.
Get efficient in performing data mining and machine learning using IBM SPSS Modeler Key FeaturesLearn how to apply machine learning techniques in the field of data scienceUnderstand when to use different data mining techniques, how to set up different analyses, and how to interpret the resultsA step-by-step approach to improving model development and performanceBook DescriptionMachine learning (ML) combined with data mining can give you amazing results in your data mining work by empowering you with several ways to look at data.
Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questionsKey FeaturesImplement solutions to 50 real-world computer vision applications using PyTorchUnderstand the theory and working mechanisms of neural network architectures and their implementationDiscover best practices using a custom library created especially for this bookBook DescriptionDeep learning is the driving force behind many recent advances in various computer vision (CV) applications.
Explore various Generative Adversarial Network architectures using the Python ecosystemKey FeaturesUse different datasets to build advanced projects in the Generative Adversarial Network domainImplement projects ranging from generating 3D shapes to a face aging applicationExplore the power of GANs to contribute in open source research and projectsBook DescriptionGenerative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data.
Take your machine learning models to the next level by learning how to leverage hyperparameter tuning, allowing you to control the model's finest detailsKey FeaturesGain a deep understanding of how hyperparameter tuning worksExplore exhaustive search, heuristic search, and Bayesian and multi-fidelity optimization methodsLearn which method should be used to solve a specific situation or problemBook DescriptionHyperparameters are an important element in building useful machine learning models.
Think about your data intelligently and ask the right questionsKey FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook DescriptionData cleaning is the all-important first step to successful data science, data analysis, and machine learning.
Leverage the power of Java and its associated machine learning libraries to build powerful predictive modelsKey FeaturesSolve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET librariesPractical examples, tips, and tricks to help you understand applied machine learning in JavaBook DescriptionAs the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations.
Updated and revised second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problemsKey FeaturesUpdated to include new algorithms and techniquesCode updated to Python 3.
This book constitutes the refereed proceedings of the 42nd German Conference on Artificial Intelligence, KI 2019, held in Kassel, Germany, in September 2019.
This book constitutes the proceedings of the 41st DAGM German Conference on Pattern Recognition, DAGM GCPR 2019, held in Dortmund, Germany, in September 2019.
This book constitutes the refereed proceedings of the 16th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2018, held in Beijing, China, in September 2018.
This book constitutes the proceedings of the 32nd Australasian Joint Conference on Artificial Intelligence, AI 2019, held in Adelaide, SA, Australia, in December 2019.
This book constitutes the proceedings of the 16th Asian Symposium on Programming Languages and Systems, APLAS 2018, held in Wellington, New Zealand, in December 2018.
This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019.
This book constitutes the proceedings of the 6th InternationalConference on Algorithms for Computational Biology, AlCoB 2019, held in Berkeley, CA, USA, in May 2019.
