Deep learning deep learning explained to your granny a guide for beginners

Author: PAT NAKAMOTO
Publisher: PAT NAKAMOTO
ISBN: 1983821357
Format: PDF, Mobi
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Ready to crank up a deep neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning' to your LinkedIn profile? Well, hold on there... Before you embark on your epic journey into the world of deep learning, there is basic theory to march through first! Take a step-by-step journey through the basics of Deep Learning, made so simple that…even your granny could understand it! What you will gain from this book: * A deep understanding of how Deep Learning works * A basics comprehension on how to build a Deep Neural Network from scratch Who this book is for: * Beginners who want to approach the topic, but are too afraid of complex math to start! What's Inside? * A general overview of Deep Learning * What are the limits of Deep Learning? * Deep Learning: the basics * Layers, Learning paradigms, Training, Validation * Main architectures and algorithms * Convolutional Neural Networks * Models for Deep Learning * Probabilistic graphic models * Restricted Boltzmann Machines * Deep Belief Networks * Available Frameworks and libraries * TensorFlow Hit download. Now!

Neural Networks and Deep Learning

Author: Pat Nakamoto
Publisher: Createspace Independent Publishing Platform
ISBN: 9781983822704
Format: PDF, ePub, Mobi
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Ready to crank up a neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning' to your LinkedIn profile? Well, hold on there... Before you embark on your epic journey into the world of deep learning, there is basic theory to march through first! Take a step-by-step journey through the basics of Neural Networks and Deep Learning, made so simple that...even your granny could understand it! What you will gain from this book: * A deep understanding of how a Neural Network and Deep Learning work * A basics comprehension on how to build a Deep Neural Network from scratch Who this book is for: * Beginners who want to approach the topic, but are too afraid of complex math to start! What's Inside? * A brief introduction to Machine Learning * Two main Types of Machine Learning Algorithms * A practical example of Unsupervised Learning * What are Neural Networks? * McCulloch-Pitts's Neuron * Types of activation function * Types of network architectures * Learning processes * Advantages and disadvantages * Let us give a memory to our Neural Network * The example of book writing Software * Deep learning: the ability of learning to learn * How does Deep Learning work? * Main architectures and algorithms * Main types of DNN * Available Frameworks and libraries * Convolutional Neural Networks * Tunnel Vision * Convolution * The right Architecture for a Neural Network * Test your Neural Network * A general overview of Deep Learning * What are the limits of Deep Learning? * Deep Learning: the basics * Layers, Learning paradigms, Training, Validation * Main architectures and algorithms * Models for Deep Learning * Probabilistic graphic models * Restricted Boltzmann Machines * Deep Belief Networks * Available Frameworks and libraries * TensorFlow Hit download. Now!

Neuronale Netze selbst programmieren

Author: Tariq Rashid
Publisher: O'Reilly
ISBN: 3960101031
Format: PDF, Kindle
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Neuronale Netze sind Schlüsselelemente des Deep Learning und der Künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Sie sind Grundlage vieler Anwendungen im Alltag wie beispielsweise Spracherkennung, Gesichtserkennung auf Fotos oder die Umwandlung von Sprache in Text. Dennoch verstehen nur wenige, wie neuronale Netze tatsächlich funktionieren. Dieses Buch nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie neuronale Netze arbeiten: - Zunächst lernen Sie die mathematischen Konzepte kennen, die den neuronalen Netzen zugrunde liegen. Dafür brauchen Sie keine tieferen Mathematikkenntnisse, denn alle mathematischen Ideen werden behutsam und mit vielen Illustrationen und Beispielen erläutert. Eine Kurzeinführung in die Analysis unterstützt Sie dabei. - Dann geht es in die Praxis: Nach einer Einführung in die populäre und leicht zu lernende Programmiersprache Python bauen Sie allmählich Ihr eigenes neuronales Netz mit Python auf. Sie bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. - Im nächsten Schritt tunen Sie die Leistung Ihres neuronalen Netzes so weit, dass es eine Zahlenerkennung von 98 % erreicht – nur mit einfachen Ideen und simplem Code. Sie testen das Netz mit Ihrer eigenen Handschrift und werfen noch einen Blick in das mysteriöse Innere eines neuronalen Netzes. - Zum Schluss lassen Sie das neuronale Netz auf einem Raspberry Pi Zero laufen. Tariq Rashid erklärt diese schwierige Materie außergewöhnlich klar und verständlich, dadurch werden neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.

Menschheit 2 0

Author: Ray Kurzweil
Publisher: Lola Books
ISBN: 3944203135
Format: PDF, ePub, Mobi
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Das Jahr 2045 markiert einen historischen Meilenstein: Es ist das Jahr, in dem der Mensch seine biologischen Begrenzungen mithilfe der Technik überwinden wird. Diese als technologische Singularität bekannt gewordene Revolution wird die Menschheit für immer verändern. Googles Chefingenieur Ray Kurzweil, dessen wahnwitzigen Visionen in den vergangenen Jahrzehnten immer wieder genau ins Schwarze trafen, zeichnet in diesem Klassiker des Transhumanismus mit beispielloser Detailwut eine bunt schillernde Momentaufnahme der technischen Evolution und legt dar, weshalb diese so bald kein Ende finden, sondern im Gegenteil immer weiter an Dynamik gewinnen wird. Daraus ergibt sich eine ebenso faszinierende wie schockierende Vision für die Zukunft der Menschheit.

Data Mining For Dummies

Author: Meta S. Brown
Publisher: John Wiley & Sons
ISBN: 1118893166
Format: PDF, Mobi
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Delve into your data for the key to success Data mining is quickly becoming integral to creating value andbusiness momentum. The ability to detect unseen patterns hidden inthe numbers exhaustively generated by day-to-day operations allowssavvy decision-makers to exploit every tool at their disposal inthe pursuit of better business. By creating models and testingwhether patterns hold up, it is possible to discover newintelligence that could change your business's entire paradigm fora more successful outcome. Data Mining for Dummies shows you why it doesn't take adata scientist to gain this advantage, and empowers averagebusiness people to start shaping a process relevant to theirbusiness's needs. In this book, you'll learn the hows and whys ofmining to the depths of your data, and how to make the case forheavier investment into data mining capabilities. The book explainsthe details of the knowledge discovery process including: Model creation, validity testing, and interpretation Effective communication of findings Available tools, both paid and open-source Data selection, transformation, and evaluation Data Mining for Dummies takes you step-by-step through areal-world data-mining project using open-source tools that allowyou to get immediate hands-on experience working with large amountsof data. You'll gain the confidence you need to start making datamining practices a routine part of your successful business. Ifyou're serious about doing everything you can to push your companyto the top, Data Mining for Dummies is your ticket toeffective data mining.

Machine Learning

Author: Herbert Jones
Publisher: Createspace Independent Publishing Platform
ISBN: 9781727831962
Format: PDF, Docs
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3 comprehensive manuscripts in 1 book Machine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More Neural Networks: An Essential Beginners Guide to Artificial Neural Networks and their Role in Machine Learning and Artificial Intelligence Deep Learning: An Essential Guide to Deep Learning for Beginners Who Want to Understand How Deep Neural Networks Work and Relate to Machine Learning and Artificial Intelligence Every day, someone is putting down a book on machine learning and giving up on learning about this revolutionary topic. How many of them miss out on furthering their career, and perhaps even the progress of our species...without even realizing? You see, most beginners make the same mistake when first delving into the topic of machine learning. They start off with a resource containing too many unrelatable facts, math, and programming lingo that will put them to sleep rather than ignite their passion. But that is about to change... This new book on machine learning will explain the concepts, methods and history behind machine learning, including how our computers became vastly more powerful but infinitely stupider than ever before and why every tech company and their grandmother want to keep track of us 24/7, siphoning data points from our electronic devices to be crunched by their programs that then become virtual crystal balls, predicting our thoughts before we even have them. Most of the book reads like science fiction because in a sense it is, far beyond what an average person would be willing to believe is happening. Here are some of the topics that are discussed in part 1 of this book: What is machine learning? What's the point of machine learning? History of machine learning Neural networks Matching the human brain Artificial Intelligence AI in literature Talking, walking robots Self-driving cars Personal voice-activated assistants Data mining Social networks Big Data Shadow profiles Biometrics Self-replicating machines And much, much more! Here are some of the topics that are discussed in part 2 of this book: Programming a smart(er) computer Composition Giving neural networks legs to stand on The magnificent wetware Personal assistants Tracking users in the real world Self-driving neural networks Taking everyone's job Quantum leap in computing Attacks on neural networks Neural network war Ghost in the machine No backlash And Much, Much More Here are some of the topics that are discussed in part 3 of this book: Improving the Scientific Method How It All Started Appeasing the Rebellious Spirits Quantum Approach To Science The Replication Crisis Evolving the Machine Brain The Future of Deep Learning Medicine with the Help of a Digital Genie And Much, Much More So if you want to learn about machine learning, click "add to cart"!

Grundz ge der Morphologie des Deutschen

Author: Hilke Elsen
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110373637
Format: PDF, ePub, Docs
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Dieses Lehrbuch zu Flexion und Wortbildung des Deutschen orientiert sich gezielt an den Studiengängen Bachelor und Master mit jeweils getrennten Kapiteln für Anfänger und Fortgeschrittene. Der Stoff ist in Module strukturiert, die den Band zusammen mit dem Glossar außerdem zu einem Nachschlagewerk zur Prüfungsvorbereitung machen. Das Buch stellt die etablierte Fachterminologie vor und behandelt morphologische Einheiten, formelle und semantische Strukturen und Verfahren der Analyse mit seltenen und unproduktiven Wortbildungsarten. Dabei findet auch die Fremdwortbildung Berücksichtigung sowie diachrone Entwicklungen und die Wortbildung der Präpositionen, Konjunktionen und Pronomen. Anhand von zahlreichen Beispielen werden die systematischen syntaktischen, semantischen, morphologischen und phonologischen Zusammenhänge deutlich, die im Verlaufe der Sprachentwicklung und beim Gebrauch der Wörter zum aktuellen Stand der Wortstrukturen führten. Problemorientierte Diskussionen, Musterlösungen, Übungsaufgaben sowie Literaturhinweise zur Vertiefung unterstützen ein selbständiges Bearbeiten des Stoffes. Daserfolgreiche Einführungswerk liegt nun in einer aktualisiertenNeuauflage vor.

Computational Neuroscience Theoretical Insights into Brain Function

Author: Paul Cisek
Publisher: Elsevier
ISBN: 9780080555027
Format: PDF, Mobi
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Computational neuroscience is a relatively new but rapidly expanding area of research which is becoming increasingly influential in shaping the way scientists think about the brain. Computational approaches have been applied at all levels of analysis, from detailed models of single-channel function, transmembrane currents, single-cell electrical activity, and neural signaling to broad theories of sensory perception, memory, and cognition. This book provides a snapshot of this exciting new field by bringing together chapters on a diversity of topics from some of its most important contributors. This includes chapters on neural coding in single cells, in small networks, and across the entire cerebral cortex, visual processing from the retina to object recognition, neural processing of auditory, vestibular, and electromagnetic stimuli, pattern generation, voluntary movement and posture, motor learning, decision-making and cognition, and algorithms for pattern recognition. Each chapter provides a bridge between a body of data on neural function and a mathematical approach used to interpret and explain that data. These contributions demonstrate how computational approaches have become an essential tool which is integral in many aspects of brain science, from the interpretation of data to the design of new experiments, and to the growth of our understanding of neural function. • Includes contributions by some of the most influential people in the field of computational neuroscience • Demonstrates how computational approaches are being used today to interpret experimental data • Covers a wide range of topics from single neurons, to neural systems, to abstract models of learning

R f r Dummies

Author: Andrie de Vries
Publisher: John Wiley & Sons
ISBN: 3527812520
Format: PDF, Docs
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Wollen Sie auch die umfangreichen Möglichkeiten von R nutzen, um Ihre Daten zu analysieren, sind sich aber nicht sicher, ob Sie mit der Programmiersprache wirklich zurechtkommen? Keine Sorge - dieses Buch zeigt Ihnen, wie es geht - selbst wenn Sie keine Vorkenntnisse in der Programmierung oder Statistik haben. Andrie de Vries und Joris Meys zeigen Ihnen Schritt für Schritt und anhand zahlreicher Beispiele, was Sie alles mit R machen können und vor allem wie Sie es machen können. Von den Grundlagen und den ersten Skripten bis hin zu komplexen statistischen Analysen und der Erstellung aussagekräftiger Grafiken. Auch fortgeschrittenere Nutzer finden in diesem Buch viele Tipps und Tricks, die Ihnen die Datenauswertung erleichtern.