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  • Simulation for Data Science with R

    Effective Data-driven Decision Making

    Harness actionable insights from your data with computational statistics and simulations using RKey Features\[\*\] Learn five different simulation techniques (Monte Carlo, Discrete Event Simulation, System Dynamics, Agent-Based Modeling, and Resampling) in-depth using real-world case studies\[\*\] A unique book that teaches you the essential and fundamental concepts in statistical modeling and ... Read more

    $41.39 USD or Free with Kobo Plus

  • Visualization and Imputation of Missing Values

    With Applications in R

    Series series Mathematics and Statistics (R0)
    This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for ... Read more

    $161.99 USD

  • Statistical Disclosure Control for Microdata

    Methods and Applications in R

    Series series Mathematics and Statistics (R0)
    This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and ... Read more

    $58.99 USD

  • Applied Compositional Data Analysis

    With Worked Examples in R

    Series series Mathematics and Statistics (R0)
    This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis, classification and regression. In addition, it considers special data structures like high-dimensional compositions ... Read more

    $143.09 USD

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

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  • Essential Math for Data Science

    Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics

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  • Python: Advanced Predictive Analytics

    Gain practical insights by exploiting data in your business to build advanced predictive modeling applications

    Gain practical insights by exploiting data in your business to build advanced predictive modeling applicationsKey FeaturesA step-by-step guide to predictive modeling including lots of tips, tricks, and best practicesLearn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and ClusteringMaster open source Python tools to build ... Read more

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  • Statistics for Machine Learning

    Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

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    Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover ... Read more

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  • Modern Time Series Forecasting with Python

    Explore industry-ready time series forecasting using modern machine learning and deep learning

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  • Fundamentals of Machine Learning for Predictive Data Analytics, second edition

    Algorithms, Worked Examples, and Case Studies

    The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and ... Read more

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    Get to grips with the statistics and math knowledge needed to enter the world of data science with Python

    by Rongpeng Li ...
    Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data using Python programmingKey FeaturesWork your way through the entire data analysis pipeline with statistics concerns in mind to make reasonable decisionsUnderstand how various data science algorithms functionBuild a solid foundation in statistics for data ... Read more

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