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 applications About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regress...
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2017
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781788992367/?ar |
| Zusammenfassung: | Gain practical insights by exploiting data in your business to build advanced predictive modeling applications About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Who This Book Is For This book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move on from a conceptual understanding of advanced analytics and become an expert in designing and building advanced analytics solutions using Python. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about predictive analytics algorithms, this book will also help you. What You Will Learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis In Detail Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic ... |
| Beschreibung: | "Learning path.". - Includes bibliographical references and index. - Online resource; title from cover (Safari, viewed February 1, 2018) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 9781788993036 1788993039 1788992369 9781788992367 |
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| spelling | Kumar, Ashish VerfasserIn aut Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications Ashish Kumar, Joseph Babcock Birmingham, UK Packt Publishing 2017 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier "Learning path.". - Includes bibliographical references and index. - Online resource; title from cover (Safari, viewed February 1, 2018) Gain practical insights by exploiting data in your business to build advanced predictive modeling applications About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Who This Book Is For This book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move on from a conceptual understanding of advanced analytics and become an expert in designing and building advanced analytics solutions using Python. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about predictive analytics algorithms, this book will also help you. What You Will Learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis In Detail Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic ... Python (Computer program language) Information visualization Application software Development Python (Langage de programmation) Visualisation de l'information Logiciels d'application ; Développement Data capture & analysis Artificial intelligence Information architecture Database design & theory Computers ; Intelligence (AI) & Semantics Computers ; Data Processing Computers ; Data Modeling & Design Application software ; Development Babcock, Joseph VerfasserIn aut |
| spellingShingle | Kumar, Ashish Babcock, Joseph Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications Python (Computer program language) Information visualization Application software Development Python (Langage de programmation) Visualisation de l'information Logiciels d'application ; Développement Data capture & analysis Artificial intelligence Information architecture Database design & theory Computers ; Intelligence (AI) & Semantics Computers ; Data Processing Computers ; Data Modeling & Design Application software ; Development |
| title | Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications |
| title_auth | Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications |
| title_exact_search | Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications |
| title_full | Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications Ashish Kumar, Joseph Babcock |
| title_fullStr | Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications Ashish Kumar, Joseph Babcock |
| title_full_unstemmed | Python advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications Ashish Kumar, Joseph Babcock |
| title_short | Python |
| title_sort | python advanced predictive analytics gain practical insights by exploiting data in your business to build advanced predictive modeling applications |
| title_sub | advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications |
| topic | Python (Computer program language) Information visualization Application software Development Python (Langage de programmation) Visualisation de l'information Logiciels d'application ; Développement Data capture & analysis Artificial intelligence Information architecture Database design & theory Computers ; Intelligence (AI) & Semantics Computers ; Data Processing Computers ; Data Modeling & Design Application software ; Development |
| topic_facet | Python (Computer program language) Information visualization Application software Development Python (Langage de programmation) Visualisation de l'information Logiciels d'application ; Développement Data capture & analysis Artificial intelligence Information architecture Database design & theory Computers ; Intelligence (AI) & Semantics Computers ; Data Processing Computers ; Data Modeling & Design Application software ; Development |
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