AutoML of incremental machine learning algorithms
This Technology Deep Dive is hosted by our member organisation, IBM. It will address the limitations of traditional batch learning algorithms in handling the challenges posed by high-frequency, high-volume Big Data and real-time monitoring. It focuses on the growing importance of Incremental Machine Learning Algorithms (IMLA) and how AutoML for IMLA differs from traditional AutoML.
This one hour masterclass, presented by Dr. Seshu Tirupathi of IBM, Ireland is tailored for individuals with basic programming knowledge in Python and experience using Jupyter notebooks, along with a familiarity with machine learning problems like classification or regression. It is ideal for data scientists, machine learning engineers, or AI enthusiasts interested in learning more about incremental machine learning algorithms (IMLA) and AutoML
Target Audience: MLOps and software engineers, data scientists, research students and researchers.
Masterclass Outline:
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Understand the importance of automated pipelines in Intelligent Machine Learning Applications (IMLA) for processing Big Data
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Gain insights into building optimized machine learning pipelines with minimal manual intervention
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Explore the role of automation in handling the growing demands of Big Data
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Learn about the power of foundation models and transformers for time series data
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Discuss challenges involved in fine-tuning transformers for specific target domains
This masterclass is part of our ‘Technical Deep Dive Masterclass’ series delivered by our member organisations on a monthly basis. If you or your organisation would like to run your own masterclass for the benefit of our community, please get in touch.
