filmov
tv
#ODSC Meetup | Topological Data Analysis: New Perspectives on Machine Learning - by Jesse Johnson
Показать описание
Abstract:
When looked at from the right perspective, many of the ideas and algorithms involved in machine learning/data science can be thought of as discovering geometric patterns and shapes in a collection of data points. I will explain how this perspective applies to some of the basic algorithms, then explore some ways in which mathematicians are using concepts from higher-dimensional abstract geometry and topology to better understand the structure of data.
About Jesse Johnson:
Before starting at Google, Jesse was a math professor studying abstract geometry and topology. He became interested in data after learning that many problems in machine learning can be posed in terms of geometry. In addition to developing a number of new algorithms by translating existing techniques from abstract geometry, Jesse began writing the Shape of Data blog to explore how geometric thinking can make the ideas behind machine learning/data mining accessible to non-experts.
When looked at from the right perspective, many of the ideas and algorithms involved in machine learning/data science can be thought of as discovering geometric patterns and shapes in a collection of data points. I will explain how this perspective applies to some of the basic algorithms, then explore some ways in which mathematicians are using concepts from higher-dimensional abstract geometry and topology to better understand the structure of data.
About Jesse Johnson:
Before starting at Google, Jesse was a math professor studying abstract geometry and topology. He became interested in data after learning that many problems in machine learning can be posed in terms of geometry. In addition to developing a number of new algorithms by translating existing techniques from abstract geometry, Jesse began writing the Shape of Data blog to explore how geometric thinking can make the ideas behind machine learning/data mining accessible to non-experts.
1:01:47
#ODSC Meetup | Topological Data Analysis: New Perspectives on Machine Learning - by Jesse Johnson
1:01:28
Meetup: Topological Data Analysis
0:08:44
ODSC Interview with Jesse Johnson
1:13:51
'Topological Data Analysis for the Working Data Scientist' - Anthony Bak @ Trulia
0:11:43
ODSC Interview with Owen Zhang
1:15:59
SVML 20141003 Topological Data Analysis with Ayasdi
1:05:25
Harish Chintakunta (2/9/16): Topological Data Analysis and Signal Processing
0:37:00
Learning and Topological Data Analysis for Advanced Data Segmentations and Predictions
0:39:37
Scaling Machine Learning with Data Mesh - SHAWN KYZER
1:04:18
Prof. Gunnar Carlsson - Topological Data Analysis and Deep Learning
0:11:55
ODSC East 2016 | Stefan Karpinski - 'Solving the Two Language Problem'
0:01:01
Netflix Data Facts with Chris Colburn | ODSC
1:01:29
Dr. Shmuel Weinberger: Topology and Data
1:22:43
Stanford Seminar Topological Data Analysis: How Ayasdi used TDA to Solve Complex Problems - The Best
1:05:03
Topological Data Analysis in Neuroscience - Lunchtime Colloquium
0:19:21
Geometric and Topological Data Analysis for Materials Discovery | AI & Topology | Vitaliy Kurlin
0:56:26
Chad Topaz (11/1/17): Topological data analysis of collective motion
0:36:54
An Introduction to Topological Data Analysis - Laber Labs Workshop
0:16:34
CogX - Topological Data Analysis and Computation | CogX
0:59:34
John Harer (10/7/14): Topological Data Analysis and Machine Learning
0:13:34
Compressed Topological Data Analysis - Hahn, Rimal
0:43:19
'Shape and Meaning' - Anthony Bak @ Ayasdi
1:02:49
Peter Bubenik (10/28/14): Statistical topological data analysis
0:05:58
Topological Data Analysis of U.S. Wildfires and COVID-19 Presentation
Комментарии