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Deep Learning
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on artificial neural networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL. Key features: Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications Explains the concepts and terminology in problem-solving with deep learning Explores the theoretical basis for ...
AN INTRODUCTION TO DEEP LEARNING
Using model architectures, complex structures, or other techniques that are generated from a range of nonlinear transformations, such as neural networks, it is an area of machine learning that is based on algorithms that aim to express high-level abstractions in data. Neural networks are one example of such an approach. In the subject of machine learning, this particular topic is referred to as classification and regression. Deep learning is an area of machine learning that is the topic of the term "deep learning," which is one of the ways that it is defined. When it comes to machine learning, it is a member of a larger family of methodologies that serve as a basis for training models by usi...
AN INTRODUCTION TO DEEP LEARNING
In deep learning, an artificial neural network (ANN) stores and processes large amounts of data. This is because artificial neural networks are used in deep learning. It is able to find both overt and covert connections across datasets. When working with deep learning, direct programming is not always necessary. Recent years have seen a meteoric rise in its popularity as a result of developments in processing power and the availability of massive datasets. This is one of the reasons why. For the reason that it was created using artificial designed to learn from large datasets. Deep Learning is a subfield of Machine Learning that use neural networks for modeling and problem solving; its devel...
Artificial Neural Networks and Machine Learning – ICANN 2023
The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.
Knowledge Discovery, Knowledge Engineering and Knowledge Management
This book constitutes the extended and revised versions of a set of selected papers from the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2021, on October 25–27, 2021. The conference was held virtually due to the COVID-19 crisis. The 9 full papers included in this book were carefully reviewed and selected from 103 submissions. The purpose of the IC3K is to bring together researchers, engineers and practitioners on the areas of Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K is composed of three co-located conferences, each specialized in at least one of the aforementioned main knowledge areas.
Internet of Things: Architectures for Enhanced Living Environments
Advances in Computers, Volume presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on - Contains novel subject matter that is relevant to computer science - Includes the expertise of contributing authors - Presents an easy to comprehend writing style
AI in Drug Discovery
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Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities
The development of software has expanded substantially in recent years. As these technologies continue to advance, well-known organizations have begun implementing these programs into the ways they conduct business. These large companies play a vital role in the economic environment, so understanding the software that they utilize is pertinent in many aspects. Researching and analyzing the tools that these corporations use will assist in the practice of software engineering and give other organizations an outline of how to successfully implement their own computational methods. Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities is an ess...
