AI/ML in Networking
Overall rating: 4.83 Instructor: 5.00 Materials: 4.83 more …
If you want to learn about the self-driving network, or about autonomous networks, or self-healing networks, or self-configuring networks… don't bother with this webinar. We will not talk about that. While it is fair to oversell a bit certain product capabilities to capture attention (and do keep in mind that the webinar author happens to be a product manager at the moment), the first priority should always be to create valuable products that deliver tangible value, and set the right expectations around them.
Artificial Intelligence (AI) and Machine Learning (ML) represents a real opportunity in networking, and has some tangible use cases. We will mention them and evaluate the good parts of AI/ML and the opportunities it brings. We will also analyze the (sometimes not so nice) reality, the bad aspects and the most ugly ones. The goal of this webinar is to give you tools and decision points to help you explore the applicability of AI/ML in your context, understand the challenges and constraints, but also identify the opportunities, and set the basis for you to start this journey, either building your own tools or using commercial ones.
The second part of the webinar focuses on Large Language Models (LLM), their implications, potential applications in the networking industry, and practical use cases. It will also help you get started with the basic tools, describe LLM network implications, and introduce LLM-powered autonomous agents.
The Author
Javier Antich has been in the Networking Industry since late 1990s. He holds a BS Degree in Telecommunication Engineering from the ETSIT at the Polytechnic University in Valencia, Executive MBA at the IE Business School, and a Data Science and Deep Learning master’s degree from the Madrid Institute of IoT. Javier is an accomplished author of the best-selling book “Machine Learning for Network and Cloud Engineers”.
Happy Campers
About the webinar
- The webinar is unique especially in the AI/ML area, because it delivers on fundamentals, without drifting into any network vendor marketing fluff.
- Jochen Bartl
- Good introduction to network-related ML
- HOCK CHEW GOH