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O'Reilly

O'Reilly

US
@oreilly
6.8K
Video Count
31.8M
Video View
200.0K
Subscriber
#22,509
United States Rank
#112,933
Global Rank
6.8K
Video Count
31.8M
Video View
200.0K
Subscriber
#22,509
United States Rank
#112,933
Global Rank
  1. Home
  2. Channel Analytics
  3. O'Reilly
O'Reilly YouTube channel subscribers:200,000- Seelive statisticsand growth insights below.
OverviewVideosOutliersStatisticsSimilar ChannelsTimelineRetention AnalyticsAbout

O'Reilly YouTube Statistics & Analytics

Subscribers
200.0K
Total Views
31.8M
Videos
6.8K
Activity
Unknown

O'Reilly Content Analysis

Content Type Distribution

Long videosLong
63%
77 videos
ShortsShorts
37%
46 videos

⚖️ This channel maintains a balanced mix of Shorts and Long videos for diverse audience engagement.

Content Categories

Primary CategoryScience & Technology
100%
Science & Technology
123(100%)

🎯 Primary focus: Science & Technology with 123 videos (100% of categorized content).

O'Reilly AI Channel Analysis

Gemini ProScore: 7.2/10

AI-powered insights analyzing content strategy, audience engagement, and growth potential.

Overall Score
7.2
Consistency
95%
Cadence
2-3/wk
Library
50

Growth Potential

7.5/10

Good content foundation. Increasing upload frequency could boost growth.

Audience Engagement

7.2/10

Moderate engagement levels. Focus on community interaction could improve metrics.

Content Strategy

7/10

Developing content strategy. Consider focusing on specific niches for better targeting.

AI Recommendations

Auto-prioritized by predicted impact

  1. 1
    Increase upload frequency to 2-3 videos per week
    High ImpactCadence
  2. 2
    Focus on SEO optimization for better discoverability
    High ImpactSEO
  3. 3
    Analyze top-performing content for pattern replication
    MediumStrategy
  4. 4
    Increase community engagement through comments and polls
    MediumEngagement

Latest Video

Short video
Local First: Simplifying App Development with Martin Kleppmann
0:49
New

Local First: Simplifying App Development with Martin Kleppmann

84
Views
2
Likes
1 week ago
Published

Taking a traditional cloud approach to data means a ton of REST calls and complex failure handling. Designing Data-Intensive Applications author Martin Kleppmann explains how going local first “massively simplifies the programming model.” #shorts Follow O'Reilly on: LinkedIn: https://www.linkedin.com/company/oreilly/ Facebook: http://facebook.com/OReilly Instagram: https://www.instagram.com/oreillymedia BlueSky: https://bsky.app/profile/oreilly.bsky.social

O'Reilly Media (Publisher) O'Reilly OReilly

Top 5 Videos

#1
Scaling AI: Still the Way to Go? with Sharon Zhou

Scaling AI: Still the Way to Go? with Sharon Zhou

1.1K
2 weeks ago
#2
Designing RL Environments for Model Training with Sharon Zhou

Designing RL Environments for Model Training with Sharon Zhou

1.1K
2 weeks ago
#3
Why You End Up Needing an Orchestrator

Why You End Up Needing an Orchestrator

1K
1 month ago
#4
Live with Tim O’Reilly: A Conversation with Computer Programmer Steve Yegge

Live with Tim O’Reilly: A Conversation with Computer Programmer Steve Yegge

904
3 weeks ago
#5
In-Context Learning vs Supervised Fine-Tuning with Sharon Zhou

In-Context Learning vs Supervised Fine-Tuning with Sharon Zhou

809
2 weeks ago

O'Reilly AI Channel Analysis

Gemini ProScore: 7.2/10

AI-powered insights analyzing content strategy, audience engagement, and growth potential.

Overall Score
7.2
Consistency
95%
Cadence
2-3/wk
Library
50

Growth Potential

7.5/10

Good content foundation. Increasing upload frequency could boost growth.

Audience Engagement

7.2/10

Moderate engagement levels. Focus on community interaction could improve metrics.

Content Strategy

7/10

Developing content strategy. Consider focusing on specific niches for better targeting.

AI Recommendations

Auto-prioritized by predicted impact

  1. 1
    Increase upload frequency to 2-3 videos per week
    High ImpactCadence
  2. 2
    Focus on SEO optimization for better discoverability
    High ImpactSEO
  3. 3
    Analyze top-performing content for pattern replication
    MediumStrategy
  4. 4
    Increase community engagement through comments and polls
    MediumEngagement

Frequently Asked Questions About O'Reilly

Data Source & Accuracy

Source: YouTube Data API v3
Accuracy: Real-time statistics from official YouTube API
Data is updated hourly and sourced directly from official APIs to ensure accuracy and reliability.

Data from YouTube Data API v3 • Updated hourly • Last updated: 04:40 AM