𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications

✍ Scribed by George A. Tsihrintzis and Lakhmi C. Jain


Publisher
Springer
Year
2020
Tongue
English
Leaves
429
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Machine Learning Paradigms: Advances in
✍ George A. Tsihrintzis, Lakhmi C. Jain πŸ“‚ Library πŸ“… 2020 πŸ› Springer International Publishing;Springer 🌐 English

<p><p>At the dawn of the 4<sup>th</sup> Industrial Revolution, the field of <i>Deep Learning</i> (a sub-field of <i>Artificial Intelligence</i> and <i>Machine Learning</i>) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse ot

Machine Learning Paradigms: Advances in
✍ Maria Virvou, Efthimios Alepis, George A. Tsihrintzis, Lakhmi C. Jain πŸ“‚ Library πŸ“… 2020 πŸ› Springer International Publishing 🌐 English

<p><p></p><p>This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education

Classification Applications with Deep Le
✍ Laith Abualigah πŸ“‚ Library πŸ“… 2022 πŸ› Springer 🌐 English

<p><span>This book is very beneficial for early researchers/faculty who want to work in deep learning and machine learning for the classification domain. It helps them study, formulate, and design their research goal by aligning the latest technologies studies’ image and data classifications. The ea

Deep Learning in Healthcare: Paradigms a
✍ Yen-Wei Chen, Lakhmi C. Jain πŸ“‚ Library πŸ“… 2020 πŸ› Springer International Publishing 🌐 English

<p><p>This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aide