WEBINAR REPLAY
| Audience: Architects, Developers
| Technical level: Introductory
What's The Role of Machine Learning In Fast Data and Streaming Applications?
With Emre Velipasaoglu, Principal Data Scientist at Lightbend, Inc.
Machine Learning (ML)–and its subset Deep Learning (DL)–have evolved in the last decade to take an often hidden role in everyday system infrastructures. From self-driving cars to real- time credit card fraud detection to real-time personalization, organizations are using ML to improve customer interactions with systems that can train themselves–using algorithms and historical data–to actively manage complex scenarios without being explicitly programmed.
Yet in isolation, even the best ML algorithm will have limited usefulness to businesses. To create advanced offerings to set your business apart from your competitors, streaming and Fast Data applications must be able to process, learn from, and respond to a never ending stream of data.
This webinar by Emre Velipasaoglu, Principal Data Scientist at Lightbend, is for busy Architects and Managers looking to get a handle on what ML is really all about, the ideal use cases for ML and how getting it right can benefit your streaming and Fast Data application architectures. At the end of this presentation, you will have learned about:
- Transformative ML technologies that we see being used today–such as fraud detection, marketing personalization–and a look at other emerging trends that will leverage ML, such as Internet of Things, Augmented Reality and Virtual Reality.
- Identifying the correct use cases for ML, i.e. understanding where machines and algorithms can help augment our human capabilities.
- Which technologies are available to you now for unlocking the value of your data for competitive advantage.
- A short overview of how Lightbend’s upcoming Fast Data Platform ties everything together to simplify your ML initiatives.
WEBINAR REPLAY
What's The Role of Machine Learning In Fast Data and Streaming Applications?
With Emre Velipasaoglu, Principal Data Scientist at Lightbend, Inc. and Hugh McKee, Global Solutions Architect at Lightbend, Inc.
Audience: Architects, Developers
Technical level: Introductory
Machine Learning (ML)–and its subset Deep Learning (DL)–have evolved in the last decade to take an often hidden role in everyday system infrastructures. From self-driving cars to real- time credit card fraud detection to real-time personalization, organizations are using ML to improve customer interactions with systems that can train themselves–using algorithms and historical data–to actively manage complex scenarios without being explicitly programmed.
Yet in isolation, even the best ML algorithm will have limited usefulness to businesses. To create advanced offerings to set your business apart from your competitors, streaming and Fast Data applications must be able to process, learn from, and respond to a never ending stream of data.
This webinar by Emre Velipasaoglu, Principal Data Scientist at Lightbend, is for busy Architects and Managers looking to get a handle on what ML is really all about, the ideal use cases for ML and how getting it right can benefit your streaming and Fast Data application architectures. At the end of this presentation, you will have learned about:
- Transformative ML technologies that we see being used today–such as fraud detection, marketing personalization–and a look at other emerging trends that will leverage ML, such as Internet of Things, Augmented Reality and Virtual Reality.
- Identifying the correct use cases for ML, i.e. understanding where machines and algorithms can help augment our human capabilities.
- Which technologies are available to you now for unlocking the value of your data for competitive advantage.
- A short overview of how Lightbend’s upcoming Fast Data Platform ties everything together to simplify your ML initiatives.
