Deep Learning – Grundlagen und Implementierung

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Author :
Publisher : O'Reilly
ISBN 13 : 3960103786
Total Pages : 252 pages
Book Rating : 4.9/5 (61 download)

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Book Synopsis Deep Learning – Grundlagen und Implementierung by : Seth Weidman

Download or read book Deep Learning – Grundlagen und Implementierung written by Seth Weidman and published by O'Reilly. This book was released on 2020-05-23 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grundprinzipien und Konzepte neuronaler Netze systematisch und verständlich erklärt Deep-Learning-Grundlagen für Data Scientists und Softwareentwickler mit Erfahrung im Machine Learning Implementierung der Deep-Learning-Konzepte mit dem beliebten Framework PyTorch Zahlreiche Codebeispiele in Python verdeutlichen die konkrete Umsetzung Dieses Buch vermittelt Ihnen das konzeptionelle und praktische Rüstzeug, um ein tiefes Verständnis für die Funktionsweise neuronaler Netze zu bekommen. Sie lernen die Grundprinzipien des Deep Learning kennen, zu deren Veranschaulichung Seth Weidman gut nachvollziehbare Konzeptmodelle entwickelt hat, die von Codebeispielen begleitet werden. Das Buch eignet sich für Data Scientists und Softwareentwickler mit Erfahrung im Machine Learning. Sie beginnen mit den Basics des Deep Learning und gelangen schnell zu den Details fortgeschrittener Architekturen, indem Sie deren Aufbau von Grund auf neu implementieren. Dabei lernen Sie mehrschichtige neuronale Netze wie Convolutional und Recurrent Neural Networks kennen. Diese neuronalen Netzwerkkonzepte setzen Sie dann mit dem beliebten Framework PyTorch praktisch um. Auf diese Weise bauen Sie ein fundiertes Wissen darüber auf, wie neuronale Netze mathematisch, rechnerisch und konzeptionell funktionieren.

Deep Learning from Scratch

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Publisher : O'Reilly Media
ISBN 13 : 1492041386
Total Pages : 253 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning from Scratch by : Seth Weidman

Download or read book Deep Learning from Scratch written by Seth Weidman and published by O'Reilly Media. This book was released on 2019-09-09 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework

Einführung in Deep Learning

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Publisher :
ISBN 13 : 9783960091363
Total Pages : 252 pages
Book Rating : 4.0/5 (913 download)

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Book Synopsis Einführung in Deep Learning by : Seth Weidman

Download or read book Einführung in Deep Learning written by Seth Weidman and published by . This book was released on 2020-05-31 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Deep Learning from the Basics

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Publisher : Packt Publishing
ISBN 13 : 9781800206137
Total Pages : 316 pages
Book Rating : 4.2/5 (61 download)

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Book Synopsis Deep Learning from the Basics by : Koki Saitoh

Download or read book Deep Learning from the Basics written by Koki Saitoh and published by Packt Publishing. This book was released on 2021-03-04 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover ways to implement various deep learning algorithms by leveraging Python and other technologiesKey Features* Learn deep learning models through several activities* Begin with simple machine learning problems, and finish by building a complex system of your own* Teach your machines to see by mastering the technologies required for image recognitionBook DescriptionDeep learning is rapidly becoming the most preferred way of solving data problems. This is thanks, in part, to its huge variety of mathematical algorithms and their ability to find patterns that are otherwise invisible to us.Deep Learning from the Basics begins with a fast-paced introduction to deep learning with Python, its definition, characteristics, and applications. You'll learn how to use the Python interpreter and the script files in your applications, and utilize NumPy and Matplotlib in your deep learning models. As you progress through the book, you'll discover backpropagation--an efficient way to calculate the gradients of weight parameters--and study multilayer perceptrons and their limitations, before, finally, implementing a three-layer neural network and calculating multidimensional arrays.By the end of the book, you'll have the knowledge to apply the relevant technologies in deep learning.What you will learn* Use Python with minimum external sources to implement deep learning programs* Study the various deep learning and neural network theories* Learn how to determine learning coefficients and the initial values of weights* Implement trends such as Batch Normalization, Dropout, and Adam* Explore applications like automatic driving, image generation, and reinforcement learningWho this book is forDeep Learning from the Basics is designed for data scientists, data analysts, and developers who want to use deep learning techniques to develop efficient solutions. This book is ideal for those who want a deeper understanding as well as an overview of the technologies. Some working knowledge of Python is a must. Knowledge of NumPy and pandas will be beneficial, but not essential.

Operations Research Proceedings 2004

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540242741
Total Pages : 504 pages
Book Rating : 4.2/5 (427 download)

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Book Synopsis Operations Research Proceedings 2004 by : Hein Fleuren

Download or read book Operations Research Proceedings 2004 written by Hein Fleuren and published by Springer Science & Business Media. This book was released on 2005-05-20 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings provide information on the most recent advances in operations research and related areas in economics, mathematics, and computer science, contributed by academics and practitioners from around the world.

Marketing and Sales Automation

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Publisher : Springer Nature
ISBN 13 : 3031200403
Total Pages : 466 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Marketing and Sales Automation by : Uwe Hannig

Download or read book Marketing and Sales Automation written by Uwe Hannig and published by Springer Nature. This book was released on 2023-05-02 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book clarifies based on latest findings and research what one needs to know about marketing and sales automation, how to manage projects to implement them, select and implement tools, and what results can be achieved. It also outlines what can be expected in the future such as the automation of corporate communication and Human Resources. The range of topics spans from the creation of a valid data base in the context of applied AI for realizing predictive intelligence and the effects of data regulations such as the European General Data Protection Regulation (GDPR) when addressing customers and prospects to recommendations for selecting and implementing the necessary IT systems. Experts also report on their experiences in regard to Conversion-rate-optimization (CRO) and provide tips and assistance on how to optimize and ensure the highest RoI for marketing and sales automation. A special focus will be placed on the dovetailing of marketing and sales and the management of the customer journey as well as the improvement of the customer experience.

Intelligent Business Process Optimization for the Service Industry

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Author :
Publisher : KIT Scientific Publishing
ISBN 13 : 3866444540
Total Pages : 334 pages
Book Rating : 4.8/5 (664 download)

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Book Synopsis Intelligent Business Process Optimization for the Service Industry by : Markus Kress

Download or read book Intelligent Business Process Optimization for the Service Industry written by Markus Kress and published by KIT Scientific Publishing. This book was released on 2014-08-13 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The company's sustainable competitive advantage derives from its capacity to create value for customers and to adapt the operational practices to changing situations. Business processes are the heart of each company. Therefore process excellence has become a key issue. This book introduces a novel approach focusing on the autonomous optimization of business processes by applying sophisticated machine learning techniques such as Relational Reinforcement Learning and Particle Swarm Optimization.

Production at the Leading Edge of Technology

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Publisher : Springer Nature
ISBN 13 : 3031473949
Total Pages : 778 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Production at the Leading Edge of Technology by : Thomas Bauernhansl

Download or read book Production at the Leading Edge of Technology written by Thomas Bauernhansl and published by Springer Nature. This book was released on 2023-11-17 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: The German Academic Association for Production Technology (WGP) annually invites researchers coming from its institutes and from industry to contribute peer reviewed papers in the field of production technology. This congress proceedings provides recent research results and findings on leading-edge manufacturing processes. Main aim of this scientific congress is to push forward existing borders in production and to provide novel solutions of "Production at the Leading Edge of Manufacturing Technology. The subtitle “Technology-Based Sustainable Production for Circular Economy” of this year’s congress emphasizes challenges for global productions in the light of climate change and resource scarcity. Different sessions were held on the topics Environmentally neutral production (e.g. energy and material efficiency) Resilient Value Creation Systems Biointelligence Digitization as an Enabler for Sustainable Production Production Technologies for a Circular Economy

Operations Research Proceedings

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Publisher :
ISBN 13 :
Total Pages : 510 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Operations Research Proceedings by :

Download or read book Operations Research Proceedings written by and published by . This book was released on 2004 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning mit Python und Keras, TensorFlow 2 und Scikit-learn

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Author :
Publisher : MITP-Verlags GmbH & Co. KG
ISBN 13 : 3747502156
Total Pages : 925 pages
Book Rating : 4.7/5 (475 download)

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Book Synopsis Machine Learning mit Python und Keras, TensorFlow 2 und Scikit-learn by : Sebastian Raschka / Vahid Mirjalili

Download or read book Machine Learning mit Python und Keras, TensorFlow 2 und Scikit-learn written by Sebastian Raschka / Vahid Mirjalili and published by MITP-Verlags GmbH & Co. KG. This book was released on 2021-03-03 with total page 925 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Datenanalyse mit ausgereiften statistischen Modellen des Machine Learnings • Anwendung der wichtigsten Algorithmen und Python-Bibliotheken wie NumPy, SciPy, Scikit-learn, Keras, TensorFlow 2, Pandas und Matplotlib • Best Practices zur Optimierung Ihrer Machine-Learning-Algorithmen Mit diesem Buch erhalten Sie eine umfassende Einführung in die Grundlagen und den effektiven Einsatz von Machine-Learning- und Deep-Learning-Algorithmen und wenden diese anhand zahlreicher Beispiele praktisch an. Dafür setzen Sie ein breites Spektrum leistungsfähiger Python-Bibliotheken ein, insbesondere Keras, TensorFlow 2 und Scikit-learn. Auch die für die praktische Anwendung unverzichtbaren mathematischen Konzepte werden verständlich und anhand zahlreicher Diagramme anschaulich erläutert. Die dritte Auflage dieses Buchs wurde für TensorFlow 2 komplett aktualisiert und berücksichtigt die jüngsten Entwicklungen und Technologien, die für Machine Learning, Neuronale Netze und Deep Learning wichtig sind. Dazu zählen insbesondere die neuen Features der Keras-API, das Synthetisieren neuer Daten mit Generative Adversarial Networks (GANs) sowie die Entscheidungsfindung per Reinforcement Learning. Ein sicherer Umgang mit Python wird vorausgesetzt.

Monetizing Data

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Publisher : John Wiley & Sons
ISBN 13 : 1119125138
Total Pages : 385 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Monetizing Data by : Andrea Ahlemeyer-Stubbe

Download or read book Monetizing Data written by Andrea Ahlemeyer-Stubbe and published by John Wiley & Sons. This book was released on 2018-04-30 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining. The authors — noted experts in the field — show how to generate extra benefit from data already collected and how to use it to solve business problems. In accessible terms, the book details ways to extract data to enhance business practices and offers information on important topics such as data handling and management, statistical methods, graphics and business issues. The text presents a wide range of illustrative case studies and examples to demonstrate how to adapt the ideas towards monetisation, no matter the size or type of organisation. The authors explain on a general level how data is cleaned and matched between data sets and how we learn from data analytics to address vital business issues. The book clearly shows how to analyse and organise data to identify people and follow and interact with them through the customer lifecycle. Monetising Data is an important resource: Focuses on different business scenarios and opportunities to turn data into value Gives an overview on how to store, manage and maintain data Presents mechanisms for using knowledge from data analytics to improve the business and increase profits Includes practical suggestions for identifying business issues from the data Written for everyone engaged in improving the performance of a company, including managers and students, Monetising Data is an essential guide for understanding and using data to enrich business practice.

Deep Learning from Scratch

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149204136X
Total Pages : 220 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning from Scratch by : Seth Weidman

Download or read book Deep Learning from Scratch written by Seth Weidman and published by "O'Reilly Media, Inc.". This book was released on 2019-09-09 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework

Programming Collective Intelligence

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 0596550685
Total Pages : 361 pages
Book Rating : 4.5/5 (965 download)

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Book Synopsis Programming Collective Intelligence by : Toby Segaran

Download or read book Programming Collective Intelligence written by Toby Segaran and published by "O'Reilly Media, Inc.". This book was released on 2007-08-16 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

Smart Services Summit

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Publisher : Springer Nature
ISBN 13 : 3030970426
Total Pages : 176 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Smart Services Summit by : Shaun West

Download or read book Smart Services Summit written by Shaun West and published by Springer Nature. This book was released on 2022-04-26 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art descriptions of smart service innovations in the industry, supported by novel scientific approaches. It gathers findings and insights presented at the fourth Smart Services Summit, held in Zurich, Switzerland, in October 2021, which primarily focused on how smart services have enabled companies to adapt during and to the COVID-19 pandemic. The book includes examples of remote and collaborative working that actively involve customers in service processes, requiring a change in mindset for more traditional firms. Moreover, it explores how services can be delivered faster and more affordable with the aid of new technologies and in collaboration with the customers, leading to new value propositions and business models and thus an evolution of smart services. Given its scope, the book offers an essential guide for practitioners and advanced students alike.

Advanced Deep Learning for Engineers and Scientists

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Publisher : Springer Nature
ISBN 13 : 3030665194
Total Pages : 294 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Advanced Deep Learning for Engineers and Scientists by : Kolla Bhanu Prakash

Download or read book Advanced Deep Learning for Engineers and Scientists written by Kolla Bhanu Prakash and published by Springer Nature. This book was released on 2021-07-24 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book. Presents practical basics to advanced concepts in deep learning and how to apply them through various projects; Discusses topics such as deep learning in smart grids and renewable energy & sustainable development; Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.

Data Mining

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Publisher : Elsevier
ISBN 13 : 0080890369
Total Pages : 665 pages
Book Rating : 4.0/5 (88 download)

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Book Synopsis Data Mining by : Ian H. Witten

Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects - Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Guide to Deep Learning Basics

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Author :
Publisher : Springer Nature
ISBN 13 : 3030375919
Total Pages : 140 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Guide to Deep Learning Basics by : Sandro Skansi

Download or read book Guide to Deep Learning Basics written by Sandro Skansi and published by Springer Nature. This book was released on 2020-01-23 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton. Topics and features: Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI Presents a philosophical case for the use of fuzzy logic approaches in AI Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI Explores philosophical questions at the intersection of AI and transhumanism This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.