A few weeks ago, we put out a call for data scientists interested in issues of race and racism, or people studying how those topics can be studied with data science methods, should get in touch to come talk to our audience about their work. This week we’re excited to bring on Todd Hendricks, Bay Area data scientist and a volunteer who reached out to tell us ... Show More
Jul 2020
So long, and thanks for all the fish
All good things must come to an end, including this podcast. This is the last episode we plan to release, and it doesn’t cover data science—it’s mostly reminiscing, thanking our wonderful audience (that’s you!), and marveling at how this thing that started out as a side project g ... Show More
35m 44s
Feb 2017
MLG 004 Algorithms - Intuition
<div> <p>Machine learning consists of three steps: prediction, error evaluation, and learning, implemented by training algorithms on large datasets to build models that can make decisions or classifications. The primary categories of machine learning algorithms are supervised, un ... Show More
23m 27s
Nov 2024
SE Radio 641: Catherine Nelson on Machine Learning in Data Science
<p><strong>Catherine Nelson</strong>, author of the new O'Reilly book, <em data-renderer-mark="true">Software Engineering for Data Scientists</em>, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and ... Show More
48m 19s
Feb 2017
MLG 002 Difference Between Artificial Intelligence, Machine Learning, Data Science
<div> <div> <p>Artificial intelligence is the automation of tasks that require human intelligence, encompassing fields like natural language processing, perception, planning, and robotics, with machine learning emerging as the primary method to recognize patterns in data and make ... Show More
1h 5m