دانلود کتاب Why AI/Data Science Projects Fail

فهرست مطالب :

Preface Introduction and Background Project Phases and Common Project Pitfalls 2.1 Tips for Managers Five Methods to Avoid Common Pitfalls 3.1 Ask Questions 3.2 Get Alignment 3.3 Keep It Simple 3.4 Leverage Explainability 3.5 Have the Conversation 3.6 Tips for Managers Define Phase 4.1 Project Charter 4.2 Supplier-Input-Process-Output-Customer (SIPOC) Analysis 4.3 Tips for Managers Making the Business Case:Assigning Value to Your Project 5.1 Data Analysis Projects 5.2 Automation Projects 5.3 Improving Business Processes 5.4 Data Mining Projects 5.5 Improved Data Science 5.6 Metrics to Dollar Conversion Acquisition and Exploration ofData Phase 6.1 Acquiring Data 6.2 Developing Data Collection Systems 6.3 Data Exploration 6.4 What Does the Customer Want to Know? 6.5 Preparing for a Report or Model 6.6 Tips for Managers Model-Building Phase 7.1 Keep it Simple 7.2 Repeatability 7.3 Leverage Explainability 7.4 Tips for Managers Interpret and communicate phase 8.1  Know Your Audience 8.2  Reports 8.3  Presentations 8.4  Models 8.5  Tips for Mangers Deployment Phase 9.1  Plan for Deployment from the Start 9.2  Documentation 9.3  Maintenance 9.4  Tips for Managers Summary of the Five Methods to Avoid Common Pitfalls 10.1 Ask Questions 10.2 Get Alignment 10.3 Keep It Simple 10.4 Leverage Explainability 10.5 Have the Conversation References Author Biography Table 1.1: Five project pitfalls Table 1.2: Alignment between data science project phases and Lean six sigma DMAIC framework Table 3.1: Connection between the methods to avoid pitfalls and the five project pitfalls Table 3.2: Questions to ask at retrospectives Table 4.1: Key components of a project charter Table 5.1: Deliverables and metrics for various types of data science projects Table 5.2: Example calculation for time saved Table 5.3: Types of waste with manufacturing and office examples Table 5.4: Common metrics and dollar conversion Table 8.1: Data science project types and typical final deliverables Table 8.2: Data visualization reading list Blank Page