Data Science for Business - Repeatable and Objective Data Science Process

Explore the Team Data Science Process (TDSP), an agile and iterative methodology for delivering predictive analytics solutions and intelligent applications efficiently, in this 21-minute conference talk. Learn how to digitalize smaller, specific manual processes by infusing them with AI, making them reusable and objective. Discover the key steps of TDSP, including business understanding, data preparation, supervised models, feature engineering, model tuning, and evaluation. Understand how to define targets, take a step back to assess progress, and deploy models effectively. Gain insights into real business examples and cases, core competencies of a data scientist, and how TDSP improves the overall data science process for organizations seeking to enhance efficiency and insights in their core business processes.

Intro
Goal of data science
Team Data Science Process
Business Understanding
The iterative process
Define a target
Data preparation
Supervised models
Feature engineering
Model tuning
Evaluation
Take a step back
The model
Deploy
Questions
Real business examples
Business example cases
Core competencies of a data scientist
How does TDSP improve