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Review some of the types of data products employed by data scientists. Use machine learning in healthcare as an area of interest and a data product to develop, probably a decision tree classifier.
1. Describe the context and needs addressed by the data product. Consider organizational, consumer, and technological needs.
2. Describe the purpose and goals of the data product. Justify your rationale with supporting evidence.
3. Explain what is to be gained by using the data product. Consider various perspectives across different industries and audiences.
4. Suggest three possible alternative types of data products that can accomplish these same goals. Identify areas in which these products could be doing better. What useful information can be gained by reviewing these?
4. Summarize key technologies you intend to use.
5. Consider how insights from religious and theological perspectives might be valuable when designing your data product. Would you approach this project differently when guided by a Christian worldview? Why or why not? Make sure to provide relevant references to Christian sources.
In SCTP, the value of the cumulative TSN in a SACK is 23. The value of the previous cumulative TSN in the SACK was 29. What is the problem?
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