HT: RC Richards
Quantitative Methods for Lawyers is the first course in a two course sequence and it assumes no prior knowledge of statistics / quantitative thinking. You will learn basic concepts and will receive an introduction to R (the open source programming language which is lingua franca of statistical computing). Those with a prior knowledge of statistics, etc. might be advised to simply start with our Legal Analytics course (which is a primer in machine learning / advanced analytics for lawyers that I teach with Michael Bommarito).
Obviously this move is pretty significant for those trying to sell machine learning in a SAAS style model / machine learning as a service (ML_AAS). Together with the significant amount of ML technology that is already in the opensource ecosystem – this will put more pressure on customization / configuration around problems with a much smaller premium on having access to certain forms of base models/algorithms.
LexPredict is an enterprise legal technology and consulting firm, specializing in the application of best-in-class processes and technologies from the technology, financial services, and logistics industries to the practice of law, compliance, insurance, and risk management.
We focus on the goals of prediction, optimization, and risk management to enable holistic organizational changes that empower legal decision-making. These changes span people and processes, software and data, and execution and education.
Yesterday I had the pleasure of participating in the Thomson Reuters Law Firm COO & CFO Forum Pre-Conference Workshop on Big Data. The half day workshop explored various way that law firms and outside counsel can use data to be better lawyers and run better businesses.
Here is the information for my panel (below) and the full program is located here.
It was my pleasure to join a world class group of corporate lawyers at the 2015 PLI Corporate Counsel Institute in NYC. Thanks to Mark Roellig (Mass Mutual), Randy Milch (Verizon) and the folks at PLI for inviting me to participate!
Pretty useful summary which is something we try to teach our students in our Legal Analytics Course (which could really be called Machine Learning for Lawyers). BTW – For those of you who emailed us, we promise to fill out the balance of the set of free, online Legal Analytics course materials in the coming months.
Perhaps some hyperbolic language in here but the basic idea is still intact … for law+economics / empirical legal studies – the causal inference versus machine learning point is expressed in detail in this paper called “Quantitative Legal Prediction.” Mike Bommarito and I have made this point in these slides, these slides, these slides, etc. Mike and I also make this point on Day 1 of our Legal Analytics Class (which really could be called “machine learning for lawyers”).