There is no question that machine learning is a key piece of the eDiscovery solution. Join this session to cut through the noise of terminology and learn the different functionalities, use cases, and methodologies necessary to evaluate the right tool for your needs. Jeremy Pickens, Ph.D. will lead an educational lecture to demystify the nomenclature, explain eDiscovery machine learning in plain language, and help attendees understand strengths and weaknesses along with workflow best practices. With nearly 50% of corporate legal teams having reported using some form of TAR already and another 80% expecting to increase spending on machine learning tools, now is the time to bring yourself up to speed.
Learn how to evaluate and compare different approaches and their relative strengths and weaknesses
Understand the terms and definitions of eDiscovery machine learning tools: TAR, Predictive Coding, CAL, Clustering & Concept Browsing
Review actual case metrics and statistical breakdowns of different workflows and their impact on the review process