Talking Machines

Talking Machines

Talking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Neil Lawrence, bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions. Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what to do with the answers.

Episodes

The Pace of Change and The Public View of ML @

📆 2017-10-05 07:02 / 00:44:12


The Long View and Learning in Person @

📆 2017-09-21 18:52 / 01:09:50


Machine Learning in the Field and Bayesian Baked Goods @

📆 2017-09-08 03:40 / 01:03:39


Data Science Africa with Dina Machuve @

📆 2017-08-11 01:33 / 00:52:13


The Church of Bayes and Collecting Data @

📆 2017-07-28 02:05 / 00:53:36


Getting a Start in ML and Applied AI at Facebook @

📆 2017-07-14 01:14 / 01:01:47


Bias Variance Dilemma for Humans and the Arm Farm @

📆 2017-06-29 18:51 / 00:54:10


Overfitting and Asking Ecological Questions with ML @

📆 2017-06-15 21:28 / 00:45:29


Graphons and "Inferencing" @

📆 2017-05-25 17:00 / 00:43:41


Hosts of Talking Machines: Neil Lawrence and Ryan Adams @

📆 2017-04-27 15:27 / 00:35:36


ANGLICAN and Probabilistic Programming @

📆 2016-09-01 17:45 / 00:46:13


Eric Lander and Restricted Boltzmann Machines @

📆 2016-08-18 19:37 / 00:55:57


Generative Art and Hamiltonian Monte Carlo @

📆 2016-08-04 16:36 / 00:49:02



Automatic Translation and t-SNE @

📆 2016-07-07 18:07 / 00:34:01


Fantasizing Cats and Data Numbers @

📆 2016-06-16 18:50 / 00:51:13


Spark and ICML @

📆 2016-06-02 19:19 / 00:41:01



Sparse Coding and MADBITS @

📆 2016-05-05 19:08 / 00:43:25


Remembering David MacKay @

📆 2016-04-21 14:12 / 00:55:15


Machine Learning and Society @

📆 2016-04-08 05:13 / 00:50:27


Software and Statistics for Machine Learning @

📆 2016-03-24 13:15 / 00:41:07


Machine Learning in Healthcare and The AlphaGo Matches @

📆 2016-03-10 17:30 / 00:50:31


AI Safety and The Legacy of Bletchley Park @

📆 2016-02-25 16:24 / 00:50:55


Robotics and Machine Learning Music Videos @

📆 2016-02-11 17:00 / 00:42:07


OpenAI and Gaussian Processes @

📆 2016-01-28 19:20 / 00:37:29


Real Human Actions and Women in Machine Learning @

📆 2016-01-14 12:35 / 01:01:31


Open Source Releases and The End of Season One @

📆 2015-11-22 21:37 / 00:42:40


Probabilistic Programming and Digital Humanities @

📆 2015-11-05 22:45 / 00:50:12


Workshops at NIPS and Crowdsourcing in Machine Learning @

📆 2015-10-22 14:53 / 00:49:45


Machine Learning Mastery and Cancer Clusters @

📆 2015-10-08 15:30 / 00:28:44


Data from Video Games and The Master Algorithm @

📆 2015-09-24 23:55 / 00:48:17


Strong AI and Autoencoders @

📆 2015-09-10 19:00 / 00:38:03


Active Learning and Machine Learning in Neuroscience @

📆 2015-08-27 17:12 / 00:55:49


Machine Learning in Biology and Getting into Grad School @

📆 2015-08-13 19:07 / 00:50:26


Machine Learning for Sports and Real Time Predictions @

📆 2015-07-30 17:06 / 00:31:08


Really Really Big Data and Machine Learning in Business @

📆 2015-07-16 18:57 / 00:25:46


Solving Intelligence and Machine Learning Fundamentals @

📆 2015-07-02 23:31 / 00:32:11


Working With Data and Machine Learning in Advertising @

📆 2015-06-18 18:35 / 00:41:11




Interdisciplinary Data and Helping Humans Be Creative @

📆 2015-05-07 18:32 / 00:36:17


Starting Simple and Machine Learning in Meds @

📆 2015-04-23 16:31 / 00:40:24


Spinning Programming Plates and Creative Algorithms @

📆 2015-04-09 13:18 / 00:37:18


The Automatic Statistician and Electrified Meat @

📆 2015-03-26 15:15 / 00:47:40


The Future of Machine Learning from the Inside Out @

📆 2015-03-13 23:16 / 00:30:14


The History of Machine Learning from the Inside Out @

📆 2015-02-26 17:24 / 00:34:36


Using Models in the Wild and Women in Machine Learning @

📆 2015-02-12 16:40 / 00:47:06


Common Sense Problems and Learning about Machine Learning @

📆 2015-01-29 15:26 / 00:42:55


Machine Learning and Magical Thinking @

📆 2015-01-15 14:52 / 00:37:10


Hello World! @

📆 2015-01-01 19:09 / 00:43:28