DataHour: Machine Learning on Live Streaming Data for AIOps

About the DataHour:

We can foresee that Internet of Things applications will raise the scale of data to an unprecedented level. People and devices (from home coffee machines to cars, buses, railway stations, and airports) are all loosely connected. Trillions of such connected components will generate a huge data ocean of live-streaming data and valuable information must be discovered from the data to help improve our quality of life and make our world a better place.

In this DataHour, Dr Ruby will discuss ML algorithms that could be applied to such large streams of real-time data, the opportunities to generate insights and the practical challenges in applying ML to these live-streaming data.

Prerequisites: The zeal for learning new technologies, and good to have a basic knowledge of Machine Learning.

Who is this DataHour for?

• Students & Freshers who want to build a career in the Data-tech domain.
• Working professionals who want to transition to the Data-tech domain.
• Data science professionals who want to accelerate their career growth

Note: E-certificates will be provided within 24 - 48 hours of the session only to those who have attended the entire webinar. Please make sure to join the zoom webinar with your correct name and email address to ensure that your certificate is properly credited to you.

Speaker:

Dr Ruby Annette

ML Engineer at Matilda Cloud Solutions in Texas, USA.

Dr Ruby Annette is a researcher, open-source project contributor and machine learning engineer with more than 13 years of experience in the R&D and software industry. Dr Ruby is working as a machine learning engineer for Matilda Cloud Solutions in Texas, USA. She is also actively involved in developing patentable solutions for AIOps (Artificial Intelligence for IT Operations). Her expertise is in fine-tuning the NLP and deep learning models to high accuracy for real-time deployment.

In her career, she has worked on applying machine learning for cloud intelligence, AIOps, and NLP for Music generation and recommender systems. She led the “Text to Sound” NLP team of the “Sound of AI”.

Connect with her on Linkedin