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Software 電子書系列

12 條結果中的 1 - 12 條 結果 结果
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  • Overview Of Bayesian Approach To Statistical Methods

    Software

    由 Vinaitheerthan Renganathan ……
    系列 series Software
    Statistical methods are being used in different fields such as Business & Economics, Engineering, Clinical & Pharmaceutical research including the emerging fields such as Machine Learning and Artificial Intelligence. Statistical methods based on the traditional frequentist approach are currently being use in these fields. With the emergence of high end computing nowadays Bayesian approach to …… 閱讀更多內容

    NT$316 TWD

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  • Machine Learning for Algorithmic Trading

    Predictive models to extract signals from market and alternative data for systematic trading strategies with Python

    由 Stefan Jansen ……
    Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format.Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading …… 閱讀更多內容

    NT$1,215 TWD 透過 Kobo Plus 免費享用

  • Bayesian Analysis with Python

    Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ

    由 Osvaldo Martin, Eric Ma, Austin Rochford ……
    Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key FeaturesA step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZA modern, practical and computational approach to Bayesian statistical modelingA tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.Book DescriptionThe second edition of …… 閱讀更多內容

    NT$1,069 TWD 透過 Kobo Plus 免費享用

  • Computer Age Statistical Inference

    Algorithms, Evidence, and Data Science

    由 Bradley Efron, Trevor Hastie ……
    系列 第 5 冊 - Institute of Mathematical Statistics Monographs
    The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating …… 閱讀更多內容

    NT$2,420 TWD

  • Python Machine Learning By Example

    The easiest way to get into machine learning

    由 Yuxi (Hayden) Liu, Ivan Idris ……
    Take tiny steps to enter the big world of data science through this interesting guideKey Features\[\*\] Learn the fundamentals of machine learning and build your own intelligent applications\[\*\] Master the art of building your own machine learning systems with this example-based practical guide\[\*\] Work with important classification and regression algorithms and other machine learning …… 閱讀更多內容

    NT$1,215 TWD 透過 Kobo Plus 免費享用

  • Data Analysis with R

    Click here to enter text.

    由 Tony Fischetti ……
    Load, wrangle, and analyze your data using the world\\'s most powerful statistical programming languageKey Features\[\*\]Load, manipulate and analyze data from different sources\[\*\]Gain a deeper understanding of fundamentals of applied statistics\[\*\]A practical guide to performing data analysis in practiceBook DescriptionFrequently the tool of choice for academics, R has spread deep into the …… 閱讀更多內容

    NT$1,341 TWD 透過 Kobo Plus 免費享用

  • Introduction to Bayesian Econometrics

    由 Edward Greenberg ……
    This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior …… 閱讀更多內容

    NT$1,659 TWD

  • Hands-On Machine Learning for Algorithmic Trading

    Design and implement investment strategies based on smart algorithms that learn from data using Python

    由 Stefan Jansen ……
    Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and KerasKey FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series …… 閱讀更多內容

    NT$1,446 TWD 透過 Kobo Plus 免費享用

  • Markov Models: An Introduction to Markov Models

    由 Steven Taylor ……
    Markov ModelsThis book will offer you an insight into the Hidden Markov Models as well as the Bayesian Networks. Additionally, by reading this book, you will also learn algorithms such as Markov Chain Sampling.Furthermore, this book will also teach you how Markov Models are very relevant when a decision problem is associated with a risk that continues over time, when the timing of occurrenc... …… 閱讀更多內容

    NT$126 TWD

  • Hidden Markov Models for Time Series

    An Introduction Using R, Second Edition

    由 Walter Zucchini, Iain L. MacDonald, Roland Langrock ……
    系列 series Chapman & Hall/CRC Monographs on Statistics and Applied Probability
    Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses.After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian …… 閱讀更多內容

    NT$2,421 TWD

  • Negative Binomial Regression

    由 Joseph M. Hilbe ……
    This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, …… 閱讀更多內容

    NT$3,209 TWD

  • Probability and Statistics for Data Science

    Math + R + Data

    由 Norman Matloff ……
    系列 series Chapman & Hall/CRC Data Science Series
    Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously:* Real datasets are used extensively.* All data analysis is supported by R coding.* Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, …… 閱讀更多內容

    NT$2,985 TWD