Learning Data Mining with Python: Harness the power of Python to analyze data and create insightful predictive models
β Scribed by Layton R.
- Tongue
- English
- Leaves
- 344
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Packt Publishing, 2015. β 344 p. β ISBN: 1784396052, 9781784396053
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.About the Author
Robert Layton has a PhD in computer science and has been an avid Python programmer for many years. He has worked closely with some of the largest companies in the world on data mining applications for real-world data and has also been published extensively in international journals and conferences. He has extensive experience in cybercrime and text-based data analytics, with a focus on behavioral modeling, authorship analysis, and automated open source intelligence. He has contributed code to a number of open source libraries, including the scikit-learn library used in this book, and was a Google Summer of Code mentor in 2014. Robert runs a data mining consultancy company called dataPipeline, providing data mining and analytics solutions to businesses in a variety of industries.
β¦ Subjects
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<p><b>Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models.</b><p><b>About This Book</b><p><li>Use a wide variety of Python libraries for practical data
"Python Data Analytics" is your comprehensive guide to leveraging the capabilities of Python for robust data exploration and analysis. Whether you're a data enthusiast, a budding data scientist, or a seasoned analyst, this book equips you with the skills and techniques to extract meaningful insights
Getting started with Python libraries -- NumPy arrays -- Statistics and linear algebra -- pandas primer -- Retrieving, processing, and storing data -- Data visualization -- Signal processing and time series -- Working with databases -- Analyzing textual data and social media -- Predictive analytics
Getting started with Python libraries -- NumPy arrays -- Statistics and linear algebra -- pandas primer -- Retrieving, processing, and storing data -- Data visualization -- Signal processing and time series -- Working with databases -- Analyzing textual data and social media -- Predictive analytics
Dive deeper into data analysis with the flexibility of Python and learn how its extensive range of scientific and mathematical libraries can be used to solve some of the toughest challenges in data analysis. Build your confidence and expertise and develop valuable skills in high demand in a world dr