Reinforcement Learning for Finance: A Python-Based Introduction

Learn how to implement and manage a modern customer data platform (CDP) through the Salesforce Data Cloud platform. This practical book provides a comprehensive overview that shows architects, administrators, developers, data engineers, and marketers how to ingest, store, and manage real-time customer data. Author Joyce Kay Avila demonstrates how to use Salesforce’s native connectors, canonical data model, and Einstein’s built-in trust layer to accelerate your time to value. You’ll learn how to leverage Salesforce’s low-code/no-code functionality to expertly build a Data Cloud foundation that unlocks the power of structured and unstructured data. Use Data Cloud tools to build your own predictive models or leverage third-party machine learning platforms like Amazon SageMaker, Google Vertex AI, and Databricks. This book will help you: Develop a plan to execute a CDP project effectively and efficiently Connect Data Cloud to external data sources and build out a Customer 360 Data Model Leverage data sharing capabilities with Snowflake, BigQuery, Databricks, and Azure Use Salesforce Data Cloud capabilities for identity resolution and segmentation Create calculated, streaming, visualization, and predictive insights Use Data Graphs to power Salesforce Einstein capabilities Learn Data Cloud best practices for all phases of the development lifecycle