Coders had already acquired proficiency in React Native, which made it a logical step to delve into the integration of machine learning within their mobile app. Instead of relying on extensive infrastructure to execute machine learning models, the team opted for TensorFlow to enable on-device processing. While they were aware that this approach might introduce latency due to the device’s computational limitations, they believed it to be the most effective way to gain hands-on experience and showcase the potential of machine learning. Their commitment to knowledge sharing led them to publish the project on GitHub, allowing others in the community to benefit from their insights and expertise.
As a tangible demonstration of their progress, the app successfully identified objects, such as pizza, as shown in the accompanying screenshot. This practical application of machine learning within the mobile app served as a testament to the team’s dedication to learning and innovation, while also providing a valuable resource for others interested in incorporating machine learning into their own projects.
Music City Coders 