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| Dateititel | Deep Learning (Adaptive Computation and Machine Learning series) |
| Veröffentlichungsdatum | |
| Sprache | Deutsch |
| ISBN-10 | 6584872328-TGV |
| Digital ISBN | 961-8065482529-NGY |
| Autor | Jil Lerch |
| Übersetzer | Udonna Faakhir |
| Seitenzahl | 197 Pages |
| Editor | Fenja Kümmel |
| Dokumententyp | EPub PDF AMZ HWP WRD |
| Dateigröße | 3.70 MB |
| Dateinamen | Deep Learning (Adaptive Computation and Machine Learning series).pdf |
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Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts ...
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. The deep learning textbook can now be ordered on Amazon. For up to date announcements, join our mailing list. Citing the book To cite this ...
Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so.
Deep Learning. Machine learning. 1. Definition . It is a subset of machine learning with the constant focus on achieving greater flexibility through considering the whole world as a nested hierarchy of concepts. It is a sub-branch of Artificial intelligence. It allows the machines to train with diverse datasets and predict based on their experiences. 2. Working mechanism. Neural networks help ...
Deep learning, a hierarchical computation model, learns the multilevel abstract representation of the data ... An evolving variant that constructs an adaptive network structure in the learning of representations, based on the network significance. BAE (Angshul, 2019) An evolving variant adding the path-loss term in the loss function based on dictionary learning. Convolutional neural network ...
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceXDeep learning is a form of machine ...
All-optical machine learning using diffractive deep neural networks. Science 361 , 1004–1008 (2018). ADS MathSciNet MATH Article Google Scholar
The following outline is provided as an overview of and topical guide to machine learning. Machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without ...