In this video I dive deep into the world of AI tools and how they can transform data analysis. AI has become an essential part of data science, helping us extract meaningful insights from complex data sets. I decided to test three popular AI tools to find out which ones excel at data analysis: Julius AI, Vizly, and the latest version of ChatGPT.

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I started with a public health data set, which is perfect for evaluating the capabilities of these AI tools. First I entered the data into Julius AI and was impressed with the range of visualizations it produced, such as the distribution of hospital codes and length of stay. One feature of Julius AI that I particularly liked is its self-correcting mechanism, which ensures that the analysis remains accurate.

Next I tested Vizly. This tool also provided insightful visualizations and added a layer of interactivity with its graphs. I was able to zoom in and out and interact with the data points, making the analysis more engaging. However, it had some limitations when dealing with more complex, unstructured data.

Finally, I turned to ChatGPT for data analysis. This tool stood out for its ability to create interactive graphs and its thorough analysis plans. One feature that set it apart was its ability to store metadata in memory and provide a step-by-step breakdown of the analysis process. ChatGPT was also able to confirm its findings by recalculating efficiency, adding an extra layer of reliability to the results.

AI helps research by making data analysis more efficient and accurate. Whether you're dealing with structured or unstructured data, these AI tools can provide valuable insights that can drive better decision making.

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TIME STAMPS
00:00 Introduction
00:09 Looking at the data
00:35 The first prompt
04:54 Text file data
11:18 Can they be broken?

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