talk on conference website
We are living in a digital era where vast amounts of data is constantly being generated, evaluated, and updated. As a result, the need for enterprises to keep up with this pace has grown and we are rapidly moving towards a more data-driven society. With the help of AI/ML technology, we have the power to make knowledgeable data driven decisions and effectively identify new trends and patterns, leading to more creative solutions and innovative approaches to problem-solving.
In light of the recent advancements in AI, particularly in predictive modeling, we now have a powerful tool at our disposal to quickly consume and analyze vast amounts of data. By using open source time series forecasting ML models like ARIMA and Prophet, we can provide more accurate predictions and insights in real-time, enabling organizations and teams to streamline processes and increase efficiency, improve and manage customer risk, and adapt to changing market conditions. In this talk we will discuss:
1. Open Source tooling for building predictive ML models (Python, Jupyter, MLFLow)
2. Time series forecasting techniques
3. Tips for managing ML workflows and model interpretations
Attendees will leave this talk with a deeper understanding of predictive ML models and how open source can empower us to be more data driven.