Главная
Study mode:
on
1
Introduction
2
Database Systems
3
Application Development
4
Overview
5
Data Preparation
6
Weak Supervision
7
Data Augmentation
8
Graph Augmentation
9
Mod Construction
10
Nas
11
Model Debugging
12
Metamorphic Testing
13
Deploying Models
14
Job Management
15
Pipeline Management
16
Pipeline Prediction
17
Feature Comparison
18
Summary
19
QA
Description:
Explore the development of user-friendly AI platforms in this conference talk from the KDD (Knowledge Discovery and Data Mining) conference. Delve into the critical components of AI systems, including database management, application development, and data preparation techniques. Learn about innovative approaches like weak supervision, data augmentation, and graph augmentation for enhancing AI model performance. Discover the intricacies of model construction, debugging, and testing, with a focus on metamorphic testing methods. Gain insights into the deployment process, job management, and pipeline management strategies. Examine the importance of pipeline prediction and feature comparison in AI systems. Conclude with a comprehensive summary and engage in a Q&A session to deepen your understanding of creating accessible and efficient AI platforms.

Towards an Easy-to-use AI Platform - Data, Algorithms, and Systems - Wei Wang

Association for Computing Machinery (ACM)
Add to list
0:00 / 0:00