Join me as I share my journey of creating a machine learning model from scratch using Kotlin, aimed at categorizing banking transactions to provide better financial insights. This session will cover the basics of neural networks, how to train and fine-tune them, and explore the different types of networks available. I'll also discuss the challenges I faced while building, training, and optimizing the model. You'll learn how I utilized Kotlin's API to create, train, and export the model for seamless integration into an Android app and iOS app. Finally, I’ll demonstrate the implementation of the model in an Android app to test its performance, offering practical insights for developers seeking to integrate machine learning into mobile applications.

Audience: Developers and AI enthusiasts
Technology: Kotlin, Python, TensorFlow
Session Duration: 30 minutes with a live demo

Join this session to explore how I built a machine learning model from scratch using Kotlin to categorize banking transactions and gain financial insights. We’ll dive into neural networks, model training, fine-tuning, and exporting models for mobile integration. The session includes a live demo showing the model in action within an Android app and iOS app, offering practical insights for developers and AI lovers alike.