내가 왕이 될 콘텐츠인가 - 콘텐츠 흥행 예측과 AI 기반 분석

Overview

Discover how SK Broadband combines AI with domain expertise to predict content success, minimizing investment risks through objective metrics and machine learning models for entertainment content performance forecasting.

Syllabus

• Introduction to AI in Content Prediction
Overview of AI applications in entertainment
Importance of predicting content success
• Understanding Content Success Metrics
Key performance indicators (KPIs) in entertainment
Objective metrics for assessing content potential
• Introduction to Machine Learning Models
Basics of machine learning for content prediction
Common algorithms used in entertainment forecasts
• Data Collection and Preprocessing
Sources of data for content analytics
Cleaning and preprocessing data for model input
• Domain Expertise Integration
Role of domain expertise in content prediction
Combining human judgment with AI models
• Building Predictive Models
Developing machine learning models for content success
Feature selection and model training
• Evaluating Model Performance
Metrics for assessing predictive accuracy
Techniques for model validation and improvement
• Case Studies and Applications
Real-world examples of content prediction
Success stories from SK Broadband
• Risk Management and Decision Making
Using predictions to minimize investment risks
Implementing AI insights in strategic decisions
• Future Trends in AI and Content Prediction
Emerging technologies and their potential impact
The evolving landscape of AI in the entertainment industry

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Subjects

Data Science