The first article of this series explained why law firms and law departments should familiarize themselves with machine learning algorithms. While discussing data sets collectible by firms or departments and software resources for the computations on those sets, that article left for later the topic of how machine learning software actually “learns.” Magic may be what many people think is the legerdemain of machine learning, but underneath the hood is not magic—it is math.
“Wait,” you might be protesting, “I’m a lawyer, and math is a foreign language! Real lawyers manage concepts, clients, legal problems and other lawyers, and let techie geeks crunch the numbers.” Those who stop reading here say, “Let’s preserve my comfort zone of the supremacy of text and intuition over numbers and probabilities.”
This content has been archived. It is available through our partners, LexisNexis® and Bloomberg Law.
To view this content, please continue to their sites.
LexisNexis® and Bloomberg Law are third party online distributors of the broad collection of current and archived versions of ALM's legal news publications. LexisNexis® and Bloomberg Law customers are able to access and use ALM's content, including content from the National Law Journal, The American Lawyer, Legaltech News, The New York Law Journal, and Corporate Counsel, as well as other sources of legal information.
For questions call 1-877-256-2472 or contact us at [email protected]