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Franke:BrainAGE
54,99 € *
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Erscheinungsdatum: 25.09.2014, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: BrainAGE, Titelzusatz: A novel machine learning approach for identifying abnormal age-related brain changes, Autor: Franke, Katja, Verlag: Südwestdeutscher Verlag für Hochschulschriften AG Co. KG, Sprache: Englisch, Rubrik: Medizin // Allgemeines, Lexika, Seiten: 168, Informationen: Paperback, Gewicht: 267 gr, Verkäufer: averdo

Anbieter: averdo
Stand: 28.09.2020
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The Strokes The new abnormal  LP  Standard
24,99 € *
zzgl. 3,95 € Versand

Erscheint auf schwarzem Vinyl im klaren Slipcase. Printed Album Art. Printed Inner Sleeve. 24x36" Poster und Downloadcode. Mit "The New Abnormal" legt die amerikanische Rockformation The Strokes endlich ein neues Album vor. Sieben Jahre sind seit ihrem letzten Longplayer "Comedown Machine" vergangen während vor vier Jahren mit "Future Present Past" die letzte EP erschienen ist. Neun fantastische Songs haben Julian Casablancas, Albert Hammond Jr. und Co aufgenommen, und zwar mit Star-Producer Rick Rubin."

Anbieter: EMP
Stand: 28.09.2020
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BrainAGE
63,99 € *
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BrainAGE ab 63.99 € als Taschenbuch: A novel machine learning approach for identifying abnormal age-related brain changes. Aus dem Bereich: Bücher, Wissenschaft, Medizin,

Anbieter: hugendubel
Stand: 28.09.2020
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Detecting Regime Change in Computational Financ...
58,95 € *
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This is the first book of its kind to build on the framework of Directional Change. The concept of Directional Change opens a whole new area of research. - From the Foreword by Dr Richard Olsen, Founder and CEO of Lykke, Co-founder of OANDA and pioneer in high-frequency finance and fintech A creative start at a novel and difficult problem for investors large and small. - Professor M. A. H. Dempster, University of Cambridge and Cambridge Systems Associates Limited Financial markets technology and the practice of trading are in a state of constant change. A book that details a completely new concept in trading, however, is very rare. This is one such book, and the authors should be applauded for producing this exciting new work. The concept and framework of Directional Change in prices is an area of research with much promise! - Dr David Norman, Founder of TTC Institute and author This book shows how AI could be a game-changer in finance. - Dr Amadeo Alentorn, Head of Research/Fund Manager at Merian Global Investors Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Anbieter: buecher
Stand: 28.09.2020
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Detecting Regime Change in Computational Financ...
58,95 € *
ggf. zzgl. Versand

This is the first book of its kind to build on the framework of Directional Change. The concept of Directional Change opens a whole new area of research. - From the Foreword by Dr Richard Olsen, Founder and CEO of Lykke, Co-founder of OANDA and pioneer in high-frequency finance and fintech A creative start at a novel and difficult problem for investors large and small. - Professor M. A. H. Dempster, University of Cambridge and Cambridge Systems Associates Limited Financial markets technology and the practice of trading are in a state of constant change. A book that details a completely new concept in trading, however, is very rare. This is one such book, and the authors should be applauded for producing this exciting new work. The concept and framework of Directional Change in prices is an area of research with much promise! - Dr David Norman, Founder of TTC Institute and author This book shows how AI could be a game-changer in finance. - Dr Amadeo Alentorn, Head of Research/Fund Manager at Merian Global Investors Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Anbieter: buecher
Stand: 28.09.2020
Zum Angebot
Detecting Regime Change in Computational Financ...
58,95 € *
ggf. zzgl. Versand

This is the first book of its kind to build on the framework of Directional Change. The concept of Directional Change opens a whole new area of research. - From the Foreword by Dr Richard Olsen, Founder and CEO of Lykke, Co-founder of OANDA and pioneer in high-frequency finance and fintech A creative start at a novel and difficult problem for investors large and small. - Professor M. A. H. Dempster, University of Cambridge and Cambridge Systems Associates Limited Financial markets technology and the practice of trading are in a state of constant change. A book that details a completely new concept in trading, however, is very rare. This is one such book, and the authors should be applauded for producing this exciting new work. The concept and framework of Directional Change in prices is an area of research with much promise! - Dr David Norman, Founder of TTC Institute and author This book shows how AI could be a game-changer in finance. - Dr Amadeo Alentorn, Head of Research/Fund Manager at Merian Global Investors Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Anbieter: buecher
Stand: 28.09.2020
Zum Angebot
Detecting Regime Change in Computational Financ...
58,95 € *
ggf. zzgl. Versand

This is the first book of its kind to build on the framework of Directional Change. The concept of Directional Change opens a whole new area of research. - From the Foreword by Dr Richard Olsen, Founder and CEO of Lykke, Co-founder of OANDA and pioneer in high-frequency finance and fintech A creative start at a novel and difficult problem for investors large and small. - Professor M. A. H. Dempster, University of Cambridge and Cambridge Systems Associates Limited Financial markets technology and the practice of trading are in a state of constant change. A book that details a completely new concept in trading, however, is very rare. This is one such book, and the authors should be applauded for producing this exciting new work. The concept and framework of Directional Change in prices is an area of research with much promise! - Dr David Norman, Founder of TTC Institute and author This book shows how AI could be a game-changer in finance. - Dr Amadeo Alentorn, Head of Research/Fund Manager at Merian Global Investors Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Anbieter: buecher
Stand: 28.09.2020
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Computing terminology
23,99 € *
ggf. zzgl. Versand

Computing terminology ab 23.99 € als Taschenbuch: Hacker Computer program Control unit Word processing Nibble Data stream Killer application Automated information system Interoperability Security kernel System integrity Machine-readable medium Indirection Abnormal end Abort. Aus dem Bereich: Bücher, Taschenbücher, Wirtschaft & Soziales,

Anbieter: hugendubel
Stand: 28.09.2020
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Autophagy: A Practical Guide to Detox Your Body...
9,95 € *
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You are about to discover how to leverage the power of autophagy to detox your body, promote muscle growth, prevent diseases, reverse the aging process, and boost your energy!Your body has in-build systems for defending itself against all manner of chronic diseases. And I’m not referring to the immune system. I’m referring to a secret system that the body uses to get rid of old and damaged cells and replacing these cells with new healthy ones. That’s not all - this system also destroys bacteria and viruses that may lead to infection and prevents normal, healthy cells from becoming cancerous. And with such a system, you could literally deal with all manner of diseases like cancer, dementia, chronic inflammation, arthritis, abnormal aging, chronic weight gain, chronic fatigue, muscle loss, and much more! This system is "autophagy".And while this system occurs naturally, there are steps you can take to maximize its effectiveness so that you get all the benefits that come with autophagy! But what exactly does autophagy do that makes it bring about each one of these benefits and more? What activities or habits enhance autophagy? How do you make your body an autophagy-inducing machine? What’s the science behind autophagy? What studies have been done to prove the effectiveness and efficiency of autophagy in bringing about various benefits?If you have these and other related questions about autophagy, this audiobook is for you, so keep reading. Autophagy covers the ins and outs of this somewhat "magical" system that can turn your health around if you make it part of your everyday life.More precisely, the audiobook will teach you:The basics of autophagy, including what it is, how it works, along with the many benefits that autophagy can bring to your body and overall well-beingThe factors responsible for increased lifespan and longevity in humans and other species, including the place of aut 1. Language: English. Narrator: Layce Gardner. Audio sample: http://samples.audible.de/bk/acx0/181214/bk_acx0_181214_sample.mp3. Digital audiobook in aax.

Anbieter: Audible
Stand: 28.09.2020
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