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Clean Architecture for AI/ML Applications using Dash and Plotly with Docker
Create enterprise-level dashboards using Dash and Plotly, learn about best practices, project structure, architectural patterns in Dash
Almost every Data Science project requires some kind of visualization, like visualizing the input data, exploratory data analysis using histograms or scatter plots, finding outliers or plotting statistics using box and whisker plots, visualizing the relationship between nodes using network diagrams, checking the relationships between variables using correlation matrices, visualization techniques to help understand relationships within high-dimensional datasets, visualizing the performance of the models, or the train history, etc.
Furthermore, data visualization may become a valuable addition to any presentation and the quickest path to understanding your data.
As you can see, data visualization is a crucial part of any Data Science project, but creating a dashboard is not a trivial task. There are lots of libraries available to generate beautiful diagrams, but if you are working in python Dash is the best choice in my opinion.
