Description

This 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