Hi Natalie Dev, Good Day.
Here are few things that you can do inorder to get the accurate resuts. Before uploading the data set to your AI model, do some data cleaning process that includes removing of missing values, outliers, and inconsistencies in the data. You can apply feature transformation method, which is transforming or combining of existing data to give more meaning. For example, let's say you have a data set of students and the marks of two subjects. By using this data we need to predict whether they will be admitted or not. And your one subject mark is in 0 to 100 and other is in 0 to 50, in this case you need to tranform the data by applying min-max scaling to scale them both between 0 and 1. You can also do squared of your dataset. In the example of subject marks we can apply Subject 1 squared (Subject 1^2) or Subject 2 squared (Subject 2^2). You can also create an interaction between the two data set by multiplying those. So in the end we will have, Subject 1 scaled, Subject 2 scaled, Subject 1 squred, subject 2 squared and the interaction between them. These will provide some additional info to our Ai to predict the exact results. You can also apply some regularization techniques like L1 and L2 to make your data more understandable for your AI. Have a feedback loop where you continously monitor the performance of your AI and make the adjustments according to the results it produce till you get the accurate results.
And in MS you have various tools to support data analysis like Azure Databricks and Azure Machine Learning. You can also use Power BI to analyze your data.
Thank You.
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