Legal BI Guy

09/17/2020

Learn about pipelines in this excerpt from my class:

The following is an excerpt from my Pluralsight Azure Machine Learning Studio course. This course covers: The new Azure Machine Learning Studio Coding in Python using Jupyter notebooks and Visual Studio Code Automated Machine Learning Read more…

09/15/2020

I have released a fully updated version of my Pluralsight class on Azure Machine learning. The new version includes modules on Automated Machine Learning and Machine Learning Pipelines.

This course will provide an introduction to the power, flexibility and scalability of Azure Machine Learning. You will learn to implement the data science process, to prepare data and integrate data sources for use in machine learning experiments.

09/11/2019

Part 3 of building pipelines using is now available. In this part, learn how to build pipelines using PySpark and the Microsoft Machine Learning Server

An overview of the Hadoop and Spark for use in machine learning experiments. Demonstration using Pyspark and the Microsoft Machine Learning Server

09/03/2019

Part 1 of my series on building pipelines using is now available. In this first part, I introduce the Hadoop and Spark ecosystems.

An overview of the Hadoop and Spark for use in machine learning experiments. Subsequent parts will cover Pyspark, SparkR and Sparklyr

09/03/2019

Part 3 of my experiment using and is now available. In this part, I cover automated patent landscaping using a neural network.

Create Machine Learning experiments by combining public data from the U.S. Patent and Trademark Office with third party and private company data

08/01/2019

Part 2 of my machine learning experiment using IPO data is now available. I demonstrate statistical tests, recursive feature elimination, indicator values, and other techniques in Python. Source code on GitHub.

Learn data science with an end-to-end legal machine learning experiment over the Ritter IPO dataset using Python, Part 2: Feature Engineering

07/29/2019

In advance of , I have created two ILTA blog posts to get you started with algorithms and the process.

https://www.iltanet.org/blogs/shawn-hainsworth1/2019/06/28/an-non-technical-introduction-to-machine-learning

https://www.iltanet.org/blogs/shawn-hainsworth1/2019/07/23/the-data-science-process

Lists all of the the blog entries

07/28/2019

Part 1 of an analysis of the Ritter IPO dataset is now available. In this experiment, I use Python to import, merge, transform and visualize two Excel datasets.

Learn data science with an end-to-end legal machine learning experiment over the Ritter IPO dataset using Python, Part 1: Data Preparation

07/28/2019

I’m excited to speak at ! Join me on Tuesday, August 20th to learn about Machine Learning and AI in Action. If you haven’t registered visit (link: http://iltacon.org) iltacon.org!

07/02/2019

My new course, Scalable Machine Learning with the Microsoft Machine Learning Server, is now available. Learn how to perform experiments with using different compute contexts including and

In this course, you will learn how to create big data machine learning experiments using the Microsoft Machine Learning Server. Detailed code examples in both R and Python demonstrate how to scale your code and work with Apache Spark and SQL Server.

05/02/2019

How Do You Maximize the Value of a Dashboard? http://ow.ly/tlT630oww8V

04/30/2019

My Blog Has Several Resources For Intelligence And In General: http://ow.ly/xHAh30oww5F

Case Studies and Resources for Data Science and Machine Learning in the Legal Industry