Angebote zu "Deep" (73 Treffer)

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Deep Learning
€ 64.99 *
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Stand: Jan 16, 2019
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Deep Learning. Das umfassende Handbuch
€ 80.00 *
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Mathematische Grundlagen für Machine und Deep Learning Umfassende Behandlung zeitgemäßer Verfahren: tiefe Feedforward-Netze, Regularisierung, Performance-Optimierung sowie CNNs, Rekurrente und Rekursive Neuronale Netze Zukunftsweisende Deep-Learning-Ansätze sowie von Ian Goodfellow neu entwickelte Konzepte wie Generative Adversarial Networks Deep Learning ist ein Teilbereich des Machine Learnings und versetzt Computer in die Lage, aus Erfahrungen zu lernen. Dieses Buch behandelt umfassend alle Aspekte, die für den Einsatz und die Anwendung von Deep Learning eine Rolle spielen: In Teil I erläutern die Autoren die mathematischen Grundlagen für Künstliche Intelligenz, Neuronale Netze, Machine Learning und Deep Learning. In Teil II werden die aktuellen in der Praxis genutzten Verfahren und Algorithmen behandelt. In Teil III geben die Autoren Einblick in aktuelle Forschungsansätze und zeigen neue zukunftsweisende Verfahren auf. Dieses Buch richtet sich an Studenten und alle, die sich in der Forschung mit Deep Learning beschäftigen sowie an Softwareentwickler und Informatiker, die Deep Learning für eigene Produkte oder Plattformen einsetzen möchten. Dabei werden Grundkenntnisse in Mathematik, Informatik und Programmierung vorausgesetzt. Teil I: Angewandte Mathematik und Grundlagen für das Machine Learning Lineare Algebra Wahrscheinlichkeits- und Informationstheorie Bayessche Statistik Numerische Berechnung Teil II: Deep-Learning-Verfahren Tiefe Feedforward-Netze Regularisierung Optimierung beim Trainieren tiefer Modelle Convolutional Neural Networks Sequenzmodellierung für Rekurrente und Rekursive Netze Praxisorientierte Methodologie Anwendungen: Computer Vision, Spracherkennung, Verarbeitung natürlicher Sprache Teil III: Deep-Learning-Forschung Lineare Faktorenmodelle Autoencoder Representation Learning Probabilistische graphische Modelle Monte-Carlo-Verfahren Die Partitionsfunktion Approximative Inferenz Tiefe generative Modelle wie Restricted Boltzmann Machines, Deep-Belief-Netze, Gerichtete Generative Netze, Variational Autoencoder u.v.m.

Anbieter: buecher.de
Stand: Jan 16, 2019
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Grokking Deep Learning
€ 50.99 *
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Key Features: ? Build neural networks that can see and understand images ? Build an A.I. that will learn to defeat you in a classic Atari game ? Hands-on Learning Written for readers with high school-level math and intermediate programming skills. Experience with Calculus is helpful but not required.

Anbieter: buecher.de
Stand: Jan 16, 2019
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Fundamentals of Deep Learning
€ 29.99 *
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Anbieter: buecher.de
Stand: Jan 16, 2019
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Deep Learning with Applications Using Python
€ 26.99 *
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Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. What You Will Learn Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Use face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Engage with chatbots using deep learning Who This Book Is For Data scientists and developers who want to adapt and build deep learning applications.

Anbieter: buecher.de
Stand: Jan 16, 2019
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Deep Learning: The Definitive Guide
€ 32.99 *
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Provides developers and data scientists working in the embedded, desktop and big data/Hadoop environments with practical information and relevant techniques on best practices and use cases in deep learning theory. Original.

Anbieter: buecher.de
Stand: Jan 16, 2019
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TensorFlow for Deep Learning
€ 62.99 *
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Anbieter: buecher.de
Stand: Jan 16, 2019
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Learn Keras for Deep Neural Networks
€ 21.99 *
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Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You´ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you´ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks , you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras. What You´ll Learn Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions. Design, develop, train, validate, and deploy deep neural networks using the Keras framework Use best practices for debugging and validating deep learning models Deploy and integrate deep learning as a service into a larger software service or product Extend deep learning principles into other popular frameworks Who This Book Is For Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.

Anbieter: buecher.de
Stand: Jan 16, 2019
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Deep Learning for Natural Language Processing
€ 25.99 *
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Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You´ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways. What You Will Learn Gain the fundamentals of deep learning and its mathematical prerequisites Discover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classification Who This Book Is For Software developers who are curious to try out deep learning with NLP.

Anbieter: buecher.de
Stand: Jan 16, 2019
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Deep Learning with R_p1
€ 35.99 *
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Key features · Understand key machine learning concepts · Set up a computer environment for deep learning · Visualize neural networks · Use recurrent neural networks for text and sequence Classification Audience You´ll need intermediate R programming skills. No previous experience with machine learning or deep learning is required.

Anbieter: buecher.de
Stand: Jan 16, 2019
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