Homelander

Inspiration

Driven by our passion for data and commitment to fostering business growth, we aim to elevate the customer experience by harnessing technology to tackle common challenges and optimize service delivery. As data systems become increasingly complex, we aim to create intuitive visualizations of customer product data, making insights more accessible and impactful.

What it does

A multifaceted data driven app that allows customers to be able to have a simplified shopping experience boosted with recommendations based on their bandwidths, network strength, regarding monthly subscriptions whilst offering companies an insight into the further statistics on the datasets and predictions on outages of data.

How we built it

For recommendations, if the wireless connections were greater than 25, we would recommend the latest fiber connections, if all devices were running at 95% bps, we would recommend a network upgrade. We found datasets with outages per city and if a city was at risk for an outage, we would recommend a battery pack and unbreakable wifi. If the total connections were greater than 25, we would recommend them preventative measures such as total security, Youtube TV, and identity theft prevention.

Challenges we ran into

We initially explored several ideas that didn’t align well with the project goals, requiring us to pivot and refocus. Additionally, integrating machine learning models with real-time visualization posed challenges in optimizing performance. The complexity of working with incomplete and noisy datasets was another obstacle we overcame.

Accomplishments that we're proud of

We made unforgivable memories while facing through change of ideas. We also learned how to be team players and communicate often.

What we learned

We learned to refine ideas early so we avoid misalignment and goals for the project. We also learned new technologies such as different machine learning models and animated designs.

What's next for Homelander

We plan to scale the platform to handle larger datasets and add new customers to the data. We will refine the recommendation model for better personalization and accuracy. We will also add a predictive model feature that will assist customers in finding a solution to their issues.

Built With

• ml
• python
• react