ML_Dashboard

Overview:

This article presents three different cases of interactive dashboards/apps that can be used to enhance data analysis and understanding. The first case focuses on using TensorBoard to visualize the features of handwritten digits in a CNN model. The second case involves creating an API framework using Flask/Python to assess the likelihood of patient readmission due to diabetes. Lastly, the article discusses designing an interactive dashboard for an audiobook company to track review scores, number of reviews, and other related information.

Features:

• MNIST_Tensorboard: Using Tensorboard to visualize the features of handwritten digits in a CNN model.
• app.py: Creating an interactive web application for clinicians to assess the likelihood of patient readmission due to diabetes using Flask/Python.
• Tableau: Designing an interactive dashboard for an audiobook company to track review scores, number of reviews, and related information.

Summary:

This article explores the use of interactive dashboards and apps for data analysis. It presents three different cases where interactive dashboards are utilized. The first case uses Tensorboard to visualize features of handwritten digits in a CNN model. The second case involves creating an API framework using Flask/Python to assess patient readmission probabilities. The third case focuses on designing an interactive dashboard for an audiobook company to track review scores, number of reviews, and related information. The installation guide provides step-by-step instructions for implementing each case.