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Book Overview & Buying
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Table Of Contents
Mastering Predictive Analytics with Python
By :
Mastering Predictive Analytics with Python
By:
Overview of this book
The volume, diversity, and speed of data available has never been greater. Powerful machine learning methods can unlock the value in this information by finding complex relationships and unanticipated trends. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications to deliver insights that are of tremendous value to their organizations.
In Mastering Predictive Analytics with Python, you will learn the process of turning raw data into powerful insights. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications and how to quickly apply these methods to your own data to create robust and scalable prediction services.
Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates not only how these methods work, but how to implement them in practice. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring the insights of predictive modeling to life
Table of Contents (11 chapters)
Preface
Free Chapter
1. From Data to Decisions – Getting Started with Analytic Applications
2. Exploratory Data Analysis and Visualization in Python
3. Finding Patterns in the Noise – Clustering and Unsupervised Learning
4. Connecting the Dots with Models – Regression Methods
5. Putting Data in its Place – Classification Methods and Analysis
6. Words and Pixels – Working with Unstructured Data
7. Learning from the Bottom Up – Deep Networks and Unsupervised Features
8. Sharing Models with Prediction Services
9. Reporting and Testing – Iterating on Analytic Systems
Index
