data science vs machine learning vs ai
Machine learning uses various techniques such as regression and supervised clustering. Deliver trusted artificial intelligence.
There Are Many Fields Under The Umbrella Of The Data Science And Sometimes These Roles Look Similar To Each Data Science Learning Data Science Machine Learning
It includes more than 30 high-performance in-database algorithms producing models for immediate use in applications.
. Because data science is a broad term for multiple disciplines machine learning fits within data science. Machine Learning in Oracle Database. Image from AppliedAI.
On the other hand the data in data science may or may not evolve from a machine or a mechanical process. AI is more trusted when multiple contributors effectively collaborate and machine learning tools provide explanation and evaluation of models. Interpretability trade-off is based on a important assumption namely that explainability is an inherent property of the model.
Data Science vs. Data scientists can develop data science and machine learning solutions using the most popular languages including Python R and SQL. In this post we will try and understand the concepts behind machine learning model evaluation metrics such as sensitivity and specificity which is used to determine the performance of the machine learning modelsThe post also describes the differences between sensitivity and specificityThe concepts have been explained using the model for predicting.
I strongly believe however that with the right interpretability techniques any machine learning model can be made more interpretable albeit at a complexity and cost which is higher for some models. Machine Learning in Oracle Database supports data exploration preparation and machine learning modeling at scale using SQL R Python REST AutoML and no-code interfaces.
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