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Covers both traditional statistical and modern machine learning models for comprehensive forecasting
Includes chapters on neural networks and the forecast value added framework for advanced techniques
Step-by-step DIY implementations in Python and Excel for practical learning
Focuses on the entire demand forecasting process, from basics to leading-edge methods
Emphasizes the scientific method and critical thinking for supply chain excellence
Summarized by Shop
Using Data Science In Order To Solve A Problem Requires A Scientific Mindset More Than Coding Skills. Data Science For Supply Chain Forecasting, Second Edition Contends That A True Scientific Method Which Includes Experimentation, Observation, And Constant Questioning Must Be Applied To Supply Chains To Achieve Excellence In Demand Foreca
Format
Print Book
Edition
Second Edition
Programming Languages
Python, Excel
Content
Four new chapters on neural networks and process management
Application Areas
Supply chain forecasting, demand forecasting, process improvement