Develop data science web app dashboards using python, data analysis, ml

Develop data science web app dashboards using python, data analysis, ml

Get Started With Dash in Python. In this tutorial, you’ll go through the end-to-end process of building a dashboard using Dash.

Get  Develop data science web app dashboards using python, data analysis, ml

My name is John and I am a data science and machine learning practitioner with more than 5 years of progressive experience in various business sectors. I am now excited to offer what I love to do the most here on Fiverr.

I can develop a very professional looking dashboard for your business, project or your idea. I can also do a detailed data analysis and data preparation prior to the dashboard development as well as the model development and application of various machine learning approaches following the best data science practices.

If you have your model and your idea or if you have your data and your idea or you have an idea and an approach for the data extraction, I am happy to setup a call to discuss your project needs in more details or you can also send me a detailed project brief with your budget, proposed timeline and project goals and app screens (just sketches) if any or just a description of the app dashboard workflow with the components you'd like to showcase in the application.

Thank you for reading. I look forward to hearing from you :)

I don’t have to convince you why we need an interactive dashboard. But what most people don’t know is that they don’t have to buy expensive licenses of Tableau or PowerBI. You don’t have to enroll in a JavaScript course either.

Dash apps allow you to build interactive dashboards purely in Python. Interestingly, it could reach heights that popular BI platforms can not. Also, you can host it on your servers and your terms.

Why Dash? Why not Tableau, Power BI, or some JavaScript library?

BI Platforms such as Tableau and PowerBI do a fantastic job. It allows even non-technical managers to do data exploration themselves. I don’t have complaints about them.

They are excellent tools to perform analysis on read-only datasets. But in large data science project, you’ll have to perform complex actions. For instance, you have to trigger a backend function and start the model retraining.

In such cases, my best solution was to build a web app from scratch. JavaScript data visualization libraries such as HighCharts are excellent tools for this. They have callbacks for almost every possible user action. I use them to send data back to the server and control it better.

But this wasn’t a walk in the park. My data science team is exceptional in Python and R but not in JavaScript. Not on web frameworks such as Django either. And that’s not enough; to build modern web apps, you need frontend web frameworks such as React.

As we progressed, we realized the harsh truth. Every new technology in our stack inflates the difficulty exponentially.

And we were fortunate to find Dash.

If you’re looking for a lightweight alternative, check out Streamlit. Read along if you need a flexible, complete Python dashboarding solution.

Now, this is how I create dazzling dashboards in Python.

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