Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)

Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)

  • ASIN: 0262039249
  • ISBN: 0262039249
  • Brand: A Bradford Book
  • Manufacturer: A Bradford Book

      Taste of Christmas: A Holiday Short Story (An Eat, Pray, Die Humorous Mystery)

      Taste of Christmas: A Holiday Short Story (An Eat, Pray, Die Humorous Mystery)

    • ASIN: B01N468RZO
    • Manufacturer: JFP Trust

        Season 2 Official Teaser

        Season 2 Official Teaser

      • ASIN: B07V82C848

          The Facts of Life: Season 4

          The Facts of Life: Season 4

        • UPC: 826663119510
        • ASIN: B001993YB8
        • Brand: Shout! Factory
        • Manufacturer: Shout! Factory
            • Brand Name: VIS Mfg#:
            • Shipping Weight: 0.36 lbs
            • Manufacturer:
            • Genre:
            • All music products are properly licensed and guaranteed

          Pilot

        • ASIN: B07GH8P89Q

            Design and Analysis of Time Series Experiments

            Design and Analysis of Time Series Experiments

          • ASIN: 0190661569
          • ISBN: 0190661569
          • Manufacturer: Oxford University Press

              The Leadership Challenge: How to Make Extraordinary Things Happen in Organizations (J-B Leadership Challenge: Kouzes/Posner)

              The Leadership Challenge: How to Make Extraordinary Things Happen in Organizations (J-B Leadership Challenge: Kouzes/Posner)

            • ASIN: B06XYZR8LZ
            • Manufacturer: Jossey-Bass

                A Field Guide to Eastern Butterflies (Peterson Field Guides) (Peterson Field Guide Series)

                A Field Guide to Eastern Butterflies (Peterson Field Guides) (Peterson Field Guide Series)

              • UPC: 046442904537
              • ASIN: 0395904536
              • ISBN: 0395904536
              • Brand: Houghton Mifflin
              • Manufacturer: Houghton Mifflin Harcourt
                  • Peterson Field Guides
                  • Peterson Eastern Butterflies

                Springer Statistics: Gaussian and Non-Gaussian Linear Time Series and Random Fields (Hardcover)

                Springer Statistics: Gaussian and Non-Gaussian Linear Time Series and Random Fields (Hardcover)

                The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.

                  Springer Statistics: Gaussian and Non-Gaussian Linear Time Series and Random Fields (Hardcover)

                Fields Institute Communications: Advances in Time Series Methods and Applications: The A. Ian McLeod Festschrift (Paperback)

                Fields Institute Communications: Advances in Time Series Methods and Applications: The A. Ian McLeod Festschrift (Paperback)

                This volume reviews and summarizes some of A. I. McLeod's significant contributions to time series analysis. It also contains original contributions to the field and to related areas by participants of the festschrift held in June 2014 and friends of Dr. McLeod. Covering a diverse range of state-of-the-art topics, this volume well balances applied and theoretical research across fourteen contributions by experts in the field. It will be of interest to researchers and practitioners in time series, econometricians, and graduate students in time series or econometrics, as well as environmental statisticians, data scientists, statisticians interested in graphical models, and researchers in quantitative risk management.--

                  Fields Institute Communications: Advances in Time Series Methods and Applications: The A. Ian McLeod Festschrift (Paperback)

                NATO Science Series B:: Quantum Fields and Quantum Space Time (Paperback)

                NATO Science Series B:: Quantum Fields and Quantum Space Time (Paperback)

                The 1996 NATO Advanced Study Institute (ASI) followed the international tradi- tion of the schools held in Cargese in 1976, 1979, 1983, 1987 and 1991. Impressive progress in quantum field theory had been made since the last school in 1991. Much of it is connected with the interplay of quantum theory and the structure of space time, including canonical gravity, black holes, string theory, application of noncommutative differential geometry, and quantum symmetries. In addition there had recently been important advances in quantum field theory which exploited the electromagnetic duality in certain supersymmetric gauge theories. The school reviewed these developments. Lectures were included to explain how the "monopole equations" of Seiberg and Witten can be exploited. They were presented by E. Rabinovici, and supplemented by an extra 2 hours of lectures by A. Bilal. Both the N = 1 and N = 2 supersymmetric Yang Mills theory and resulting equivalences between field theories with different gauge group were discussed in detail. There are several roads to quantum space time and a unification of quantum theory and gravity. There is increasing evidence that canonical gravity might be a consistent theory after all when treated in. a nonperturbative fashion. H. Nicolai presented a series of introductory lectures. He dealt in detail with an integrable model which is obtained by dimensional reduction in the presence of a symmetry.

                  NATO Science Series B:: Quantum Fields and Quantum Space Time (Paperback)

                Chapman & Hall/CRC Monographs on Statistics and Applied Prob: Time Series Models: In Econometrics, Finance and Other Fields (Hardcover)

                Chapman & Hall/CRC Monographs on Statistics and Applied Prob: Time Series Models: In Econometrics, Finance and Other Fields (Hardcover)

                The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds. The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book. The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader.

                  Chapman & Hall/CRC Monographs on Statistics and Applied Prob: Time Series Models: In Econometrics, Finance and Other Fields (Hardcover)

                Parallel Lifetimes : Fluctuations in the Quantum Field: Fireside Series Volume 3 No. 3

                Parallel Lifetimes : Fluctuations in the Quantum Field: Fireside Series Volume 3 No. 3

                Part of Ramtha's Fireside Series collection library on the topic of parallel universes and creating dramatic change in our life using the principles of quantum physics. A shift in quantum state brings a parallel lifetime, and now everything in that lifetime is different. The relationship to you and your environment is lifted, for what compelled you before is not a compelling influence in the new shift. You are now in a parallel existence. In the parallel existence our mind does not leave our body behind in the old state but rather the body can also live in parallel existences because it is made of quantum material. It is now shifted into the new hall, the new life, and everything is different. What becomes apparent is that the climax that governed your life once before is now at rest. The old climax is not apparent in the new life and its influences are not seen in people, places, things, times, and events. That is the truth. This knowledge is the key to the kingdom of heaven. Ramtha

                  Part of Ramtha's Fireside Series collection library on the topic of parallel universes and creating dramatic change in our life using the principles of quantum physics. A shift in quantum state brings a parallel lifetime, and now everything in that lifetime is different. The relationship to you and your environment is lifted, for what compelled you before is not a compelling influence in the new shift. You are now in a parallel existence. In the parallel existence our mind does not leave our body behind in the old state but rather the body can also live in parallel existences because it is made of quantum material. It is now shifted into the new hall, the new life, and everything is different. What becomes apparent is that the climax that governed your life once before is now at rest. The old climax is not apparent in the new life and its influences are not seen in people, places, things, times, and events. That is the truth. This knowledge is the key to the kingdom of heaven. Ramtha

                Practical Time Series Analysis: Prediction with Statistics and Machine Learning (Paperback)

                Practical Time Series Analysis: Prediction with Statistics and Machine Learning (Paperback)

                Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase.Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly.You'll get the guidance you need to confidently: Find and wrangle time series dataUndertake exploratory time series data analysisStore temporal dataSimulate time series dataGenerate and select features for a time seriesMeasure errorForecast and classify time series with machine or deep learningEvaluate accuracy and performance

                  Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase.Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly.You'll get the guidance you need to confidently: Find and wrangle time series dataUndertake exploratory time series data analysisStore temporal dataSimulate time series dataGenerate and select features for a time seriesMeasure errorForecast and classify time series with machine or deep learningEvaluate accuracy and performance

                NATO Science Series B:: Quantum Fields and Quantum Space Time (Hardcover)

                NATO Science Series B:: Quantum Fields and Quantum Space Time (Hardcover)

                The 1996 NATO Advanced Study Institute (ASI) followed the international tradi- tion of the schools held in Cargese in 1976, 1979, 1983, 1987 and 1991. Impressive progress in quantum field theory had been made since the last school in 1991. Much of it is connected with the interplay of quantum theory and the structure of space time, including canonical gravity, black holes, string theory, application of noncommutative differential geometry, and quantum symmetries. In addition there had recently been important advances in quantum field theory which exploited the electromagnetic duality in certain supersymmetric gauge theories. The school reviewed these developments. Lectures were included to explain how the "monopole equations" of Seiberg and Witten can be exploited. They were presented by E. Rabinovici, and supplemented by an extra 2 hours of lectures by A. Bilal. Both the N = 1 and N = 2 supersymmetric Yang Mills theory and resulting equivalences between field theories with different gauge group were discussed in detail. There are several roads to quantum space time and a unification of quantum theory and gravity. There is increasing evidence that canonical gravity might be a consistent theory after all when treated in. a nonperturbative fashion. H. Nicolai presented a series of introductory lectures. He dealt in detail with an integrable model which is obtained by dimensional reduction in the presence of a symmetry.

                  NATO Science Series B:: Quantum Fields and Quantum Space Time (Hardcover)

                Synthesis Lectures on Data Mining and Knowledge Discovery: Exploratory Causal Analysis with Time Series Data (Paperback)

                Synthesis Lectures on Data Mining and Knowledge Discovery: Exploratory Causal Analysis with Time Series Data (Paperback)

                Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments. Data analysis techniques are required for identifying causal information and relationships directly from such observational data. This need has led to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in time series data sets. Exploratory causal analysis (ECA) provides a framework for exploring potential causal structures in time series data sets and is characterized by a myopic goal to determine which data series from a given set of series might be seen as the primary driver. In this work, ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.

                  Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments. Data analysis techniques are required for identifying causal information and relationships directly from such observational data. This need has led to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in time series data sets. Exploratory causal analysis (ECA) provides a framework for exploring potential causal structures in time series data sets and is characterized by a myopic goal to determine which data series from a given set of series might be seen as the primary driver. In this work, ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.
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