Sched.com Conference Mobile Apps
Data Tech
has ended
Create Your Own Event
Data Tech
-
Saved To
My Schedule
Use the event Sched to plan your day and rate the sessions you attend.
View venue map
Schedule
Simple
Expanded
Grid
By Venue
Speakers
Sponsors
Startups
Map
Search
or browse by date + venue
0 - Panel/Showcase
1 - Business
2 - Mostly Business
3 - Business & Technical
4 - More Technical
5 - Very Technical
menu
Menu
Log in
Schedule
Speakers
Sponsors
Startups
Map
Search
← Back
MR
Megan Reichert
General Mills
Data Scientist
meg.linsmeier@gmail.com
Thursday
, May 30
9:00am CDT
Connecting Data to Decisions: Where to Start with Modern Analytics
(A) Auditorium
Robotic Process Automation (RPA): The Path to AI
(F) P0838
9:45am CDT
Do-It-Yourself Interactive Data Visualization: Starting Simple (and Keeping It That Way)
(A) Auditorium
10:45am CDT
Why Marketing Analytics Fails (and How to Do It Right)
(C) A2564 - A2566
From Data Science to Knowledge Engineering: How Graphs Change Everything
(A) Auditorium
Power the Personalized Recommendation with Deep Learning and Pre-trained Embeddings.
(G) P1808
11:30am CDT
Deliberations on Scientific and Methodological Aspects of Machine Learning
(H) P1838
Systematic Innovation in Data Science
(I) K1450 (Fireside)
1:15pm CDT
Come On, Get SHAPpy: Interpretable Machine Learning with SHAP
(E) P0806 A&B
Hyper-Segmentation for Automated Insights Across Industries
(D) P0808 A&B
Machine-Learned School Dropout Early Warning at Scale
(F) P0838
2:15pm CDT
Modern Agriculture: Redefining AI
(E) P0806 A&B
Powerful Data from Unexpected Places
(B) Garden Room
3:15pm CDT
Human-Centered Data Science
(A) Auditorium
Probabilistic programming for investigation and discovery
(D) P0808 A&B
Timezone
Data Tech
America/Chicago
Filter By Venue
Normandale Partnership Center, 9700 France Ave So, Bloomington, MN 55431
Sort schedule by Venue
(A) Auditorium
(B) Garden Room
(C) A2564 - A2566
(D) P0808 A&B
(E) P0806 A&B
(F) P0838
(G) P1808
(H) P1838
(I) K1450 (Fireside)
Filter By Type
0 - Panel/Showcase
1 - Business
2 - Mostly Business
3 - Business & Technical
4 - More Technical
5 - Very Technical