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Linear Digressions

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 8 de 16

Git for Data Scientists 03/06/2018
Analytics Maturity 20/05/2018
SHAP: Shapley Values in Machine Learning 13/05/2018
Game Theory for Model Interpretability: Shapley Values 07/05/2018
AutoML 30/04/2018
CPUs, GPUs, TPUs: Hardware for Deep Learning 23/04/2018
A Technical Introduction to Capsule Networks 16/04/2018
A Conceptual Introduction to Capsule Networks 09/04/2018
Convolutional Neural Nets 02/04/2018
Google Flu Trends 26/03/2018
How to pick projects for a professional data science team 19/03/2018
Autoencoders 12/03/2018
When Private Data Isn't Private Anymore 05/03/2018
What makes a machine learning algorithm "superhuman"? 26/02/2018
Open Data and Open Science 19/02/2018
Defining the quality of a machine learning production system 12/02/2018
Auto-generating websites with deep learning 04/02/2018
The Case for Learned Index Structures, Part 2: Hash Maps and Bloom Filters 29/01/2018
The Case for Learned Index Structures, Part 1: B-Trees 22/01/2018
Challenges with Using Machine Learning to Classify Chest X-Rays 15/01/2018
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