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Python Data Mining Cookbook: Over 95 recipes for extracting hidden insights from your data using NumPy, pandas, and scikit-learn
Leverage the power of data mining in Python to generate actionable insights from your data
Key FeaturesExplore powerful libraries in Python such as scikit-learn and pandas, for efficient data miningUncover the complexities of advanced data mining methods and integrate them into your business applicationsDiscover quick solutions to the common as well as tricky problems encountered during data miningBook DescriptionMost organizations today are drowning in a deluge of data and failing to extract any value from it. To tackle this challenge, the Python Data Mining Cookbook provides numerous solutions to help you gain insights from large volumes of data and build smart and predictive applications for improving business processes.
Packed with over 95 solution-based recipes, this book is a practical toolkit of data mining methods to extract patterns and knowledge from data using one of the most popular languages, Python. The recipes in this book will help you to understand how to extract, transform and model large data sets. Along with case studies, the book will cover in-depth techniques to guide you through working with real-world complex data sets, which are high-dimensional, unstructured and voluminous. Next, with the help of applications in time series, text mining, and web mining, you’ll be able to practice exploratory data mining, sequence mining, and cluster analysis. You’ll also use libraries such as NumPy, pandas, SciPy, and Plotly, which will assist you in data mining.
By the end of this book, you will have become accustomed to various data mining methods and techniques, and their application in Python.
What you will learnAnswer complex business questions using different data mining methodsWork with pandas, Matplotlib, NumPy, SciPy and scikit-learnPerform association mining, anomaly detection and cluster analysis in PythonBuild classification and regression models to predict continuous and discrete valuesDevelop data mining solutions for time series, text, web, audio and image data using PythonBuild an end-to-end data mining pipeline and deploy models on cloud Who This Book Is ForIf you are a data scientist, analyst or a data engineer and want quick solutions to common data mining problems in Python, this book is for you. Basic knowledge of Python programming and familiarity with data manipulation will help you in getting the most out of this book.
Key FeaturesExplore powerful libraries in Python such as scikit-learn and pandas, for efficient data miningUncover the complexities of advanced data mining methods and integrate them into your business applicationsDiscover quick solutions to the common as well as tricky problems encountered during data miningBook DescriptionMost organizations today are drowning in a deluge of data and failing to extract any value from it. To tackle this challenge, the Python Data Mining Cookbook provides numerous solutions to help you gain insights from large volumes of data and build smart and predictive applications for improving business processes.
Packed with over 95 solution-based recipes, this book is a practical toolkit of data mining methods to extract patterns and knowledge from data using one of the most popular languages, Python. The recipes in this book will help you to understand how to extract, transform and model large data sets. Along with case studies, the book will cover in-depth techniques to guide you through working with real-world complex data sets, which are high-dimensional, unstructured and voluminous. Next, with the help of applications in time series, text mining, and web mining, you’ll be able to practice exploratory data mining, sequence mining, and cluster analysis. You’ll also use libraries such as NumPy, pandas, SciPy, and Plotly, which will assist you in data mining.
By the end of this book, you will have become accustomed to various data mining methods and techniques, and their application in Python.
What you will learnAnswer complex business questions using different data mining methodsWork with pandas, Matplotlib, NumPy, SciPy and scikit-learnPerform association mining, anomaly detection and cluster analysis in PythonBuild classification and regression models to predict continuous and discrete valuesDevelop data mining solutions for time series, text, web, audio and image data using PythonBuild an end-to-end data mining pipeline and deploy models on cloud Who This Book Is ForIf you are a data scientist, analyst or a data engineer and want quick solutions to common data mining problems in Python, this book is for you. Basic knowledge of Python programming and familiarity with data manipulation will help you in getting the most out of this book.
439 pages, Kindle Edition
Published October 9, 2020
1 person want to read
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