Feature Engineering Made Easy: Identify unique features from your dataset in order to build powerful machine learning systems

    Description

    A perfect guide to speed up the predicting power of machine learning algorithms

    Key Features: 

    • Design, discover, and create dynamic, efficient features for your machine learning application
    • Understand your data in-depth and derive astonishing data insights with the help of this Guide
    • Grasp powerful feature-engineering techniques and build machine learning systems

    Book Description: 

    Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective.

    You will start with understanding your data-often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data.

    By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization.

    What You Will Learn: 

    Identify and leverage different feature types

    Clean features in data to improve predictive power

    Understand why and how to perform feature selection, and model error analysis

    Leverage domain knowledge to construct new features

    Deliver features based on mathematical insights

    Use machine-learning algorithms to construct features

    Master feature engineering and optimization

    Harness feature engineering for real world applications through a structured case study

    Who this book is for: 

    If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python scripting would be enough to get started with this book.

    Feature Engineering Made Easy: Identify unique features from your dataset in order to build powerful machine learning systems

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      A perfect guide to speed up the predicting power of machine learning algorithms Key Features:  Design, discover, and create dynamic,... Read more

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        Description

        A perfect guide to speed up the predicting power of machine learning algorithms

        Key Features: 

        • Design, discover, and create dynamic, efficient features for your machine learning application
        • Understand your data in-depth and derive astonishing data insights with the help of this Guide
        • Grasp powerful feature-engineering techniques and build machine learning systems

        Book Description: 

        Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective.

        You will start with understanding your data-often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data.

        By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization.

        What You Will Learn: 

        Identify and leverage different feature types

        Clean features in data to improve predictive power

        Understand why and how to perform feature selection, and model error analysis

        Leverage domain knowledge to construct new features

        Deliver features based on mathematical insights

        Use machine-learning algorithms to construct features

        Master feature engineering and optimization

        Harness feature engineering for real world applications through a structured case study

        Who this book is for: 

        If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python scripting would be enough to get started with this book.

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