Practical Data Analysis

“Practical Data Analysis” uses a case-study based approach to explore the real-world applications of open source data analysis tools and techniques. Specifically, the following topics are covered in this book:

1. Open Source Data Analysis Tools and Techniques.

2. A Beginner’s Guide to “Python” for Data Analysis.

3. Implementing Custom Search Engines On The Fly.

4. Visualising Missing Data.

5. Sentiment Analysis and Named Entity Recognition.

6. Automatic Document Classification, Clustering and Summarisation.

7. Fraud Detection Using Machine Learning Techniques.

8. Forecasting - Using Data to Map the Future.

9. Continuous Monitoring and Real-Time Analytics.

10. Creating a Robot for Interacting with Web Applications.