
Learning Data Mining with Python
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
Key Features
Use a wide variety of Python libraries for practical data mining purposes.
Learn how to find, manipulate, analyze, and visualize data using Python.
Step-by-step instructions on data mining techniques with Python that have real-world applications.
Book DescriptionThis book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.What you will learn
[*] Apply data mining concepts to real-world problems
[*] Predict the outcome of sports matches based on past results
[*] Determine the author of a document based on their writing style
[*] Use APIs to download datasets from social media and other online services
[*] Find and extract good features from difficult datasets
[*] Create models that solve real-world problems
[*] Design and develop data mining applications using a variety of datasets
[*] Perform object detection in images using Deep Neural Networks
[*] Find meaningful insights from your data through intuitive visualizations
[*] Compute on big data, including real-time data from the internet
Who this book is forIf you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected.
More details
Other editions
Additional editions

Person
Content
Getting Started with data mining
Classification using scikit-learn estimators
Predicting Sports Winners with Decision Trees
Book Recommendations using Affinity Analysis
Features and scikit-learn transformers
Social media spam detection using Naive Bayes
Follow recommendations using graph mining
Beating CAPTCHAs with Neural Networks
Authorship attribution
Clustering news articles
Object Detection in images using Deep Neural Networks
Working with Big Data
Appendix: Next Steps
System requirements
File format: ePUB
Copy protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (not Kindle).
The file format ePub works well for novels and non-fiction books – i.e., „flowing” text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our ebook Help page.