Dapper Data
En podkast av Dapper Data
Kategorier:
97 Episoder
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Let the User's Voice Guide you - Episode #57 w/ Matt Young
Publisert: 8.5.2022 -
Design Psychology & Data Visualization - Episode #56 w/ Thomas Watkins
Publisert: 29.4.2022 -
ROI Driven Marketing - Episode #55 w/ Mary Cate Spires
Publisert: 13.4.2022 -
DataKitchen and Dev Ops - Episode #54 w/ Chris Bergh
Publisert: 23.3.2022 -
Data Fluency and Education - Episode #53 w/ Kevin Hanegan
Publisert: 17.3.2022 -
Data Visualization and Storytelling - Episode #52 w/ Lee Feinberg
Publisert: 21.2.2022 -
Measuring Cough as Clinical Evidence - Episode #51 w/ Joe brew
Publisert: 27.1.2022 -
Data Integrity for Your Business - Episode #50 w/ Verl Allen
Publisert: 6.1.2022 -
Realizing the Full Potential of Their Data - Episode #49 w/ Douwe Maan
Publisert: 2.1.2022 -
AI, Neuroscience and Continual Learning - Episode #48 w/ Keiland Cooper
Publisert: 3.12.2021 -
Data Integration from Multiple Sources - Episode #47 w/ Michel Tricot
Publisert: 26.11.2021 -
Data Driven Digital Marketing - Episode #46 w/ Wendell Jordan
Publisert: 19.11.2021 -
AI vs Human Intelligence - Episode #45 w/ Mark Kerzner
Publisert: 15.11.2021 -
The Value of AI in Education, Religion and STEM - Episode #44 w/ Slater Victoroff (Part II)
Publisert: 5.11.2021 -
The Value of AI in Education, Religion and STEM from a CTO's Perspective - Episode #43 w/ Slater Victoroff (Part I)
Publisert: 5.11.2021 -
A Data-Driven Entrepreneurial Mindset - Episode #42 w/ Alex Sanfilippo
Publisert: 29.9.2021 -
Data-Driven Decision Making from a CEO's Perspective - Episode #41 w/ Larry Fisher
Publisert: 13.7.2021 -
Deep Learning with Audio Data and Audio Data Analysis - Episode #40 w/ Graham Brown
Publisert: 7.7.2021 -
The Deepfakes and Hard Truths - Episode #39 w/ Dr. Ilke Demir
Publisert: 23.6.2021 -
The Next Gen Data Scientist - Episode #38 w/ Lexi Vessels
Publisert: 13.5.2021
This podcast provides knowledge sharing for data-driven listeners interested in understanding how data impacts the world in many ways . There are so many aspects to data (i.e. programming, statistics, machine learning, artificial intelligence, data visualizations, and more), but there is also the everyday data side (i.e. social media, money, sex, love, diseases, sports and more). I am touching on each and every one of them in a Dapper kind of way.
