This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research.
This book reviews the development of physics-based modeling and sensor-based data fusion for optimizing medical decision making in connection with spatiotemporal cardiovascular disease processes.
This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks.
This book constitutes the proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019.
This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering.
This book is for those who wish to understand how Python debugging is and can be used to develop robust and reliable AI, machine learning, and cloud computing software.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020.
Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python.
Skip the theory and get the most out of Tensorflow to build production-ready machine learning modelsKey FeaturesExploit the features of Tensorflow to build and deploy machine learning modelsTrain neural networks to tackle real-world problems in Computer Vision and NLPHandy techniques to write production-ready code for your Tensorflow modelsBook DescriptionTensorFlow is an open source software library for Machine Intelligence.
This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020.
The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.
Cover all the machine learning techniques relevant for forecasting problems, ranging from univariate and multivariate time series to supervised learning, to state-of-the-art deep forecasting models such as LSTMs, recurrent neural networks, Facebook's open-source Prophet model, and Amazon's DeepAR model.
Solve challenging data science problems by mastering cutting-edge machine learning techniques in PythonAbout This BookResolve complex machine learning problems and explore deep learningLearn to use Python code for implementing a range of machine learning algorithms and techniquesA practical tutorial that tackles real-world computing problems through a rigorous and effective approachWho This Book Is ForThis title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science.
Nowadays bioinformaticians and geneticists are faced with myriad high-throughput data usually presenting the characteristics of uncertainty, high dimensionality and large complexity.
As you move data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure your organization meets compliance requirements.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020.
Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively.
This book provides a practical guide on annotating emotions in natural language data and showcases how these annotations can improve Natural Language Processing (NLP) and Natural Language Understanding (NLU) models and applications.
This book constitutes the refereed proceedings of the First International Conference on Quantitative Ethnography, ICQE 2019, held in Madison, Wisconsin, USA, in October 2019.
Unlock the potential of AI in your organization with this updated, must-read guide, and discover how to leverage AI to drive innovation, improve efficiency, and gain a competitive edge.
This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by School of Electronics and Engineering, VIT - AP University, Amaravati, Andhra Pradesh, India, during 5-6 January 2024.
This book constitutes the proceedings of the 15th International Symposium on Bioinformatics Research and Applications, ISBRA 2019, held in Barcelona, Spain, in June 2019.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.
This book constitutes the proceedings of the First IAPR International Conference on Discrete Geometry and Mathematical Morphology, DGMM 2021, which was held during May 24-27, 2021, in Uppsala, Sweden.
This book includes high-quality research papers presented at the Seventh International Conference on Innovative Computing and Communication (ICICC 2024), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on 16-17 February 2024.
The two-volume set LNCS 12572 and 1273 constitutes the thoroughly refereed proceedings of the 27th International Conference on MultiMedia Modeling, MMM 2021, held in Prague, Czech Republic, in June2021.
This volume constitutes the proceedings of the 19th International Workshop on Digital Forensics and Watermarking, IWDW 2020, held in Melbourne, VIC, Australia, in November 2020.
A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory.
This second volume of the three-volume set (CCIS 1193, CCIS 1194, and CCIS 1195) constitutes the refereed proceedings of the First International Conference on Applied Technologies, ICAT 2019, held in Quito, Ecuador, in December 2019.
Vertiefendes Wissen von Deep Learning über Computer Vision bis Natural Language Processing- Schließt die Lücke zwischen Grundlagen und Profiwissen- Einfache, prägnante Erklärungen zu wichtigen und aktuellen Themen- Mit Übungsaufgaben sowie Codebeispielen auf GitHub Sie verfügen bereits über Grundkenntnisse zu maschinellem Lernen und künstlicher Intelligenz, haben aber viele Fragen und wollen tiefer in wesentliche und aktuelle Konzepte eintauchen?
