Towards an Easy-to-use AI Platform - Data, Algorithms, and Systems - Wei Wang
Association for Computing Machinery (ACM) via YouTube
Overview
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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.
Syllabus
Introduction
Database Systems
Application Development
Overview
Data Preparation
Weak Supervision
Data Augmentation
Graph Augmentation
Mod Construction
Nas
Model Debugging
Metamorphic Testing
Deploying Models
Job Management
Pipeline Management
Pipeline Prediction
Feature Comparison
Summary
QA
Taught by
Association for Computing Machinery (ACM)