Learning Data Mining with Python
Layton, Robert
Vendu par Lucky's Textbooks, Dallas, TX, Etats-Unis
Vendeur AbeBooks depuis 22 juillet 2022
Neuf(s) - Couverture souple
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Ajouter au panierVendu par Lucky's Textbooks, Dallas, TX, Etats-Unis
Vendeur AbeBooks depuis 22 juillet 2022
Etat : Neuf
Quantité disponible : Plus de 20 disponibles
Ajouter au panierN° de réf. du vendeur ABLIING23Mar2912160166252
Harness the power of Python to analyze data and create insightful predictive models
If you are a programmer who wants to get started with data mining, then this book is for you.
The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis.
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems.
There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK.
Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.
Harness the power of Python to analyze data and create insightful predictive models
About This Book
Who This Book Is For
If you are a programmer who wants to get started with data mining, then this book is for you.
What You Will Learn
In Detail
The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis.
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems.
There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK.
Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.
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