Web Data Mining With Python

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Web Data Mining with Python

Author: Dr. Ranjana Rajnish
language: en
Publisher: BPB Publications
Release Date: 2023-01-31
Explore different web mining techniques to discover patterns, structures, and information from the web KEY FEATURES ● A complete overview of the basic and advanced concepts of Web mining. ● Work with easy-to-use open-source Python libraries for Web mining. ● Get familiar with the various beneficial areas and applications of Web mining. DESCRIPTION Data Science is the fastest growing job across the globe and is predicted to create 11.5 million jobs by 2026, so job seekers with this skill set have a lot of opportunities. One of the most sought areas in the field of Data Science is mining information from the web. If you are an aspiring Data Scientist looking to learn different Web mining techniques, then this book is for you. This book starts by covering the key concepts of Web mining and its taxonomy. It then explores the basics of Web scraping, its uses and components followed by topics like legal aspects related to scraping, data extraction and pre-processing, scraping dynamic websites, and CAPTCHA. The book also introduces you to the concept of Opinion mining and Web structure mining. Furthermore, it covers Web graph mining, Web information extraction, Web search and hyperlinks, Hyperlink Induced Topic Search (HITS) search, and partitioning algorithms that are used for Web mining. Towards the end, the book will teach you different mining techniques to discover interesting usage patterns from Web data. By the end of the book, you will master the art of data extraction using Python. WHAT YOU WILL LEARN ● Learn how to scrape data from any website with Python. ● Get familiar with the concepts of Opinion Mining and Sentiment Analysis. ● Use Web structure mining to discover structure information from the web. ● Learn how to collect and analyze social media data using Python. ● Use Web usage mining for predicting users' browsing behaviors. WHO THIS BOOK IS FOR The book is for anyone who wants to learn Web mining. Aspiring Data Scientists, Data Engineers, and Data Analysts who want to master Web mining will find this book very helpful. TABLE OF CONTENTS 1. Web Mining—An Introduction 2. Web Mining Taxonomy 3. Prominent Applications with Web Mining 4. Python Fundamentals 5. Web Scraping 6. Web Opinion Mining 7. Web Structure Mining 8. Social Network Analysis in Python 9. Web Usage Mining
Learning Data Mining with Python

About This Book Learn data mining in practical terms, using a wide variety of libraries and techniques Learn how to find, manipulate, and analyze data using Python Step-by-step instructions on creating real-world applications of data mining techniques 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 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 Set up reproducible experiments and generate robust results Recommend movies, online celebrities, and news articles based on personal preferences Compute on big data, including real-time data from the Internet 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.
Web Scraping with Python

Author: Ryan Mitchell
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2015-06-15
Learn web scraping and crawling techniques to access data from any web source in any format. Teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing.