AI Net Conference 2019
Date: April 9 - 11, 2019
Venue: Marriott Conference Center, Paris, France
Exploring new frontiersThe Second Edition of AI Net will be held 9/11 April, 2019 in Paris.
The conference will confirm its position as a leader event in AI and Machine Learning applied to the telecom area.
AI and Machine Learning can be practically used in all networking areas, such as fault isolation, intrusion detection, event corelation, log analysis, capacity planning or design optimization.
The 2019 edition will explore next frontier areas/use cases enabled by these new approaches.
Indeed, SDN and NFV is bringing about programmability by decoupling control plane from the network devices and running softwarized network function on commodity hardware. The SDN-NFV controller is expected to play a key role for service provider network management by programming their customized network management policy. This controller requires computational intelligence.
During the past several years there have been remarkable advancement in academic research for applying machine learning to network management. Machine learning is applied to diversified data including traffic flow, performance, quality, syslog, configuration file, trouble tickets, SNS.
AI Net 2019 will address the latest advances made by operators, developers and equipment vendors in this domain.
2019 Agenda SessionsAI and Machine Learning can be practically used in all networking areas, such as fault isolation, intrusion detection, event corelation, log analysis, capacity planning or design optimization.
The 2019 edition will explore next frontier areas/use cases enabled by these new approaches. The agenda will address the following sessions:
- Data Collect
- Telemetry, Big Data Storage and Handling
- Statistical analysis, Machine Learning
- Deep Learning algorithmics vs. Deterministic solutions
- Intend-based Approaches
- Automation and Self-driving
- Use cases
- Security issues
Network Data Science Platform Round TableThe networking industry is experiencing an increasing number of platform developments to exploit Machine learning algorithms with network data.
Some come from established hardware and software vendors, and some from startups focusing on this very niche market.
This round table will provide a perspective on motivations for such platforms, compare the various strategies from vendors or opensource initiatives, explain the value added compared to generic multi-industry data science platform, describe a picture of use cases already addressed and coming trends, and show how far these platforms are open to embrace the growing ecosystem innovation of AI applied to networks.
Hand-on TutorialThe aim of this tutorial will be to explore the different machine learning phases with open source tools related to artificial intelligence.
- Installation steps of Python or R environment related to machine learning
- Raw data transformation into tabular format
- Data analysis and Feature extraction
- Problem framing : e.g. prediction, classification or clustering
- Model selection, configuration and set-up
- Model Training
- Model execution and results interpretation