Description
•Presents the main concepts in data analytics, using tools developed in Python
•Designed for use by beginners and seasoned programmers alike
•Provides the tools, alongside solved examples with steps that the reader can easily reproduce and adapt to their needs
•Focuses one practical use of the tools rather than on lengthy theoretical explanations
•Includes a Python Primer
Table of Contents
The Trials and Tribulations of a Data Scientist. Python: For Something Completely Different. The Machine that Goes "Ping": Machine Learning and Pattern Recognition. The Relationship Conundrum: Regression. Jackalopes and Hares: Clustering. Decisions, Decisions: Hierarchical Clustering, Decision Trees and Ensable Techniques. Less is More: Dimensionality Reduction. Kernel Tricks under the Sleeve: Support Vector Machines. Pipelines in Scikit-learn.
