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  Differential and Complex Geometry: Origins Abstractions and Embeddings

  Differential and Complex Geometry: Origins Abstractions and Embeddings ab 138.99 € als gebundene Ausgabe: 1st ed. 2017. Aus dem Bereich: Bücher, Wissenschaft, Mathematik,

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  • Price: 138.99 EUR excl. shipping
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  Differential and Complex Geometry: Origins Abstractions and Embeddings

  Differential and Complex Geometry: Origins Abstractions and Embeddings ab 138.99 € als Taschenbuch: Softcover reprint of the original 1st ed. 2017. Aus dem Bereich: Bücher, Taschenbücher, Naturwissenschaft,

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  • Price: 138.99 EUR excl. shipping
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  Compactifying Moduli Spaces for Abelian Varieties

  This volume presents the construction of canonical modular compactifications of moduli spaces for polarized Abelian varieties (possibly with level structure), building on the earlier work of Alexeev, Nakamura, and Namikawa. This provides a different approach to compactifying these spaces than the more classical approach using toroical embeddings, which are not canonical. There are two main new contributions in this monograph: (1) The introduction of logarithmic geometry as understood by Fontaine, Illusie, and Kato to the study of degenerating Abelian varieties; and (2) the construction of canonical compactifications for moduli spaces with higher degree polarizations based on stack-theoretic techniques and a study of the theta group.

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  • Price: 40.99 EUR excl. shipping
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  Representation Learning

  Representation Learning ab 138.99 € als pdf eBook: Propositionalization and Embeddings. Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik,

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  • Price: 138.99 EUR excl. shipping
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  Working Memory in Sentence Comprehension

  Working Memory in Sentence Comprehension ab 52.99 € als epub eBook: Processing Hindi Center Embeddings. Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Sprachwissenschaften,

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  • Price: 52.99 EUR excl. shipping
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  Natural Language Processing with PyTorch (eBook, ePUB)

  Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If youre a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations.Explore computational graphs and the supervised learning paradigmMaster the basics of the PyTorch optimized tensor manipulation libraryGet an overview of traditional NLP concepts and methodsLearn the basic ideas involved in building neural networksUse embeddings to represent words, sentences, documents, and other featuresExplore sequence prediction and generate sequence-to-sequence modelsLearn design patterns for building production NLP systems

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  • Price: 36.95 EUR excl. shipping
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  Python Text Mining

  Natural Language Processing (NLP) has proven to be useful in a wide range of applications. Because of this, extracting information from text data sets requires attention to methods, techniques, and approaches. 'Python Text Mining' includes a number of application cases, demonstrations, and approaches that will help you deepen your understanding of feature extraction from data sets. You will get an understanding of good information retrieval, a critical step in accomplishing many machine learning tasks. We will learn to classify text into discrete segments solely on the basis of model properties, not on the basis of user-supplied criteria. The book will walk you through many methodologies, such as classification, that will enable you to rapidly construct recommendation engines, subject segmentation, and sentiment analysis applications. Toward the end, we will also look at machine translation and transfer learning. By the end of this book, you'll know exactly how to gather web-based text, process it, and then apply it to the development of NLP applications. 1. Basic Text Processing Techniques 2. Text to Numbers 3. Word Embeddings 4. Topic Modeling 5. Unsupervised Sentiment Classification 6. Text Classification Using ML 7. Text Classification Using Deep learning 8. Recommendation engine 9. Transfer Learning

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  • Price: 40.99 EUR excl. shipping
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  Deep Learning Kochbuch

  Lassen Sie sich von Deep Learning nicht abschrecken! Dank Frameworks wie Keras und TensorFlow ist der schnelle Einstieg in die Entwicklung von Deep-Learning-Anwendungen nun auch für Softwareentwickler ohne umfassende Machine-Learning-Kenntnisse möglich. Mit den Rezepten aus diesem Buch lernen Sie, typische Aufgabenstellungen des Deep Learning zu lösen, wie etwa die Klassifizierung und Generierung von Texten, Bildern und Musik.Jedes Kapitel behandelt ein Projekt, wie z.B. das Trainieren eines Empfehlungssystems für Musik. Schritt für Schritt wird gezeigt, wie das jeweilige Projekt umgesetzt wird. Darüber hinaus beschreibt der Autor Douwe Osinga zahlreiche Techniken, die Ihnen helfen, wenn Sie einmal nicht mehr weiterwissen. Alle Codebeispiele sind in Python geschrieben und auf GitHub als Python-Notebooks frei verfügbar.Aus dem Inhalt:- Entwickeln Sie Deep-Learning-Anwendungen, die Nutzern einen echten Mehrwert bieten- Berechnen Sie Ähnlichkeiten von Texten mithilfe von Word-Embeddings- Erstellen Sie ein Empfehlungssystem für Filme basierend auf Wikipedia-Links- Visualisieren Sie die internen Vorgänge einer künstlichen Intelligenz, um nachvollziehen zu können, wie diese arbeitet- Entwickeln Sie ein Modell, das passende Emojis für Textpassagen vorschlägt- Realisieren Sie einen Reverse-Image-Search-Dienst mithilfe von vortrainierten Netzwerken- Vergleichen Sie, wie Generative Adversarial Networks, Autoencoder und LSTM-Netzwerke Icons erzeugen- Trainieren Sie ein Klassifikationsmodell für Musikstile und lassen Sie es Musikstücke dementsprechend zuordnen"Dieses Buch bietet einen großartigen Einstiegin Deep Learning für alle, denen praktische Ergebnisse wichtiger sind als die Theorie. Es hat dem Entwicklungsteam meines neuen Musik-Tech-Startups Weav dabei geholfen, schnell mit Deep Learning zu starten. Dieses Buch ist perfekt geeignet für jeden, der Interessean praxisorientiertem Machine Learning hat."- Lars Rasmussen, Mitbegründer von Google Maps

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  • Price: 35.90 EUR excl. shipping
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  Python Text Mining: Perform Text Processing, Word Embedding, Text Classification and Machine Translation (eBook, ePUB)

  Make use of the most advanced machine learning techniques to perform NLP and feature extraction KEY FEATURES ● Learn about pre-trained models, deep learning, and transfer learning for NLP applications.● All-in-one knowledge guide for feature engineering, NLP models, and pre-processing techniques.● Includes use cases, enterprise deployments, and a range of Python based demonstrations. DESCRIPTION Natural Language Processing (NLP) has proven to be useful in a wide range of applications. Because of this, extracting information from text data sets requires attention to methods, techniques, and approaches.'Python Text Mining' includes a number of application cases, demonstrations, and approaches that will help you deepen your understanding of feature extraction from data sets. You will get an understanding of good information retrieval, a critical step in accomplishing many machine learning tasks. We will learn to classify text into discrete segments solely on the basis of model properties, not on the basis of user-supplied criteria. The book will walk you through many methodologies, such as classification, that will enable you to rapidly construct recommendation engines, subject segmentation, and sentiment analysis applications. Toward the end, we will also look at machine translation and transfer learning. By the end of this book, you'll know exactly how to gather web-based text, process it, and then apply it to the development of NLP applications. WHAT YOU WILL LEARN● Practice how to process raw data and transform it into a usable format.● Best techniques to convert text to vectors and then transform into word embeddings.● Unleash ML and DL techniques to perform sentiment analysis.● Build modern recommendation engines using classification techniques. WHO THIS BOOK IS FORThis book is a good place to start with examples, explanations, and exercises for anyone interested in learning more about advanced text mining and natural language processing techniques. It is suggested but not required that you have some prior programming experience. AUTHOR BIO Alexandra George is an NLP trainer and has main experience in solving real-world NLP applications in Salesforce. He is an engineer, and high-tech who primarily works on data science, analytics, application development, and building intelligent systems. Alexandra research focuses on data mining, text mining as well as Machine Learning and Deep Learning applications.

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  • Price: 9.49 EUR excl. shipping
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  Homogeneous Spaces and Equivariant Embeddings

  Homogeneous Spaces and Equivariant Embeddings - Edition: ab 128.49 €

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  • Price: 128.49 EUR excl. shipping

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