This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and ...
But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How?
This book fills a sorely-needed gap in the existing literature by not sacrificing depth for breadth, presenting proofs of major theorems and subsequent derivations, as well as providing a copious amount of Python code.
Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization.
Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much aboutmachine learningapriori.
Now it is time to unleash AI on the administrative, planning and even creative procedures in marketing, sales and management. This book provides an easy-to-understand guide to assessing the value and potential of AI and Algorithmics.
Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights.
This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences.