Linear Digressions

Por: Katie Malone

Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. 896520

320 episodios disponibles

Latest episodes of the podcast Linear Digressions

Mostrando página 6 de 16

The Language Model Too Dangerous to Release 25/03/2019

The cathedral and the bazaar 17/03/2019

AlphaStar 11/03/2019

Are machine learning engineers the new data scientists? 04/03/2019

Interview with Alex Radovic, particle physicist turned machine learning researcher 25/02/2019

K Nearest Neighbors 17/02/2019

Not every deep learning paper is great. Is that a problem? 11/02/2019

The Assumptions of Ordinary Least Squares 03/02/2019

Quantile Regression 28/01/2019

Heterogeneous Treatment Effects 20/01/2019

Pre-training language models for natural language processing problems 14/01/2019

Facial Recognition, Society, and the Law 07/01/2019

Re-release: Word2Vec 31/12/2018

Re - Release: The Cold Start Problem 23/12/2018

Convex (and non-convex) Optimization 17/12/2018

The Normal Distribution and the Central Limit Theorem 09/12/2018

Software 2.0 02/12/2018

Limitations of Deep Nets for Computer Vision 18/11/2018

Building Data Science Teams 12/11/2018

Optimized Optimized Web Crawling 04/11/2018

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