A curated collection of learning resources for Generative AI, Machine Learning, Agentic AI, LLMs, RAG, Fine-tuning, MLOps, and more.
C-Rank Grade: B (Solid) - 51/100
External PR Merge Rate: 100%
Response Time: 17h
First Timer Success: -
viveknaskar/everything-ai-ml has a recorded first-timer success rate of 0.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in viveknaskar/everything-ai-ml respond to incoming external pull requests in approximately 16.8 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 51.0 places viveknaskar/everything-ai-ml in the B tier.
The external contributor pull request merge rate for viveknaskar/everything-ai-ml is 100.0%, based on public PR activity from non-core contributors.
viveknaskar/everything-ai-ml does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
A curated collection of learning resources for Generative AI, Machine Learning, Agentic AI, LLMs, RAG, Fine-tuning, MLOps, and more.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/viveknaskar/everything-ai-ml?utm_source=github&utm_medium=badge)
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No cached good first issues currently tracked for viveknaskar/everything-ai-ml.
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When evaluating whether to contribute to viveknaskar/everything-ai-ml, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of viveknaskar/everything-ai-ml acknowledge new external contributions in approximately 16 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 100.0% were successfully merged into the primary branch.
viveknaskar/everything-ai-ml has a recorded first-timer success rate of 0.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~16 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 51.0 places viveknaskar/everything-ai-ml in the Solid tier.
The external pull request merge rate is 100.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
viveknaskar/everything-ai-ml does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for viveknaskar/everything-ai-ml are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.