In this video, we're peeling back the onion on data collection and the costs and tradeoffs of data sampling. Machine learning demands a wealth of data, but every design decision during collection affects the final output of an ML model. Join along as GT makes up new metrics like PUs.
- Category
- Extreme Networks
- Tags
- machine learning, ai, artificial intelligence
Be the first to comment
Up Next
Autoplay
-
22:02
Data Collection and Preparation: Embracing Digital Transformation - Episode 18 | Intel Business
-
18:32
Demonstrating the OmniSwitch AOS Ansible Collection
-
08:20
Build a Big Data Analytics Pipeline Using Modern Data Architecture | Amazon Web Services
-
01:48
CER Trace Collection
-
12:28
The Perils of Data Collection - Data Pipeline Collection, Part 1
-
06:36
SBB Cargo: Data Collection and Processing with Serverless Analytics Services
-
08:19
Collection Group Queries in Firestore
-
04:42
Xylem: Serverless Event-Driven IOT Data Collection
-
03:08
Making Better Decisions with Data - Data collection and analysis | Amazon Web Services
-
02:51
Nexus 9000 NXOS Log Collection
-
12:25
How to Set Up WooCommerce Product Filters for Your Online Store
-
08:51
Best AI Content Writers in 2025: Our Top Picks
-
07:05
How to Set Up Email on Apple Mail in Minutes | Hostinger
-
14:47
How to Create a Professional Fitness Website With Ease
-
10:15
How to Host an Ark Server: Hostinger Tutorial
-
14:14
How to Build a Small Business Website | From Zero to Launch
-
17:31
10 Hobbies for Students That ACTUALLY Make You Money
-
05:49
SSH Connection Refused: 6 Methods to Fix It (Hostinger Tutorial)
-
17:01
How to Create a Business Website with AI | Fast & Easy!
-
12:56
How to Build a WordPress Website With AI