Chapter 9. Case studies
This chapter covers
- Review of the topics in this book
- How two companies using machine learning improved their business
- Case study 1: Implementing a single machine learning project in your company
- Case study 2: Implementing machine learning at the heart of everything your company does
Throughout the book, you have used AWS SageMaker to build solutions to common business problems. The solutions have covered a broad range of scenarios and approaches:
- Using XGBoost supervised learning to solve an approval routing challenge
- Reformatting data so that you could use XGBoost again, but this time to predict customer churn
- Using BlazingText and Natural Language Processing (NLP) to identify whether a tweet should be escalated ...
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