Comparison
HPOBench vs Awesome-AI-Data-Guided-Projects
Verdict
Pick HPOBench if hPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios; pick Awesome-AI-Data-Guided-Projects if awesome-AI-Data-Guided-Projects is a curated list featuring projects for building conversational chatbots using large language models and fine-tuning LLMs with LoRA, suitable for portfolio-building in AI.
Markdown twin · HPOBench alternatives · Awesome-AI-Data-Guided-Projects alternatives
GraphCanon updated Oct 2, 2026
7views this month
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Trust & integrity
| Signal | HPOBench | Awesome-AI-Data-Guided-Projects |
|---|---|---|
| Maintenance | Dormant (498d since push) As of Oct 2, 2026 · github_public_v1 | Dormant (870d since push) As of Sep 23, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 2, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 23, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- HPOBench
- A collection of hyperparameter optimization benchmark problems
- Awesome-AI-Data-Guided-Projects
- A curated list of data science & AI guided projects for portfolio-building
Stars
- HPOBench
- 173
- Awesome-AI-Data-Guided-Projects
- 724
Forks
- HPOBench
- 36
- Awesome-AI-Data-Guided-Projects
- 152
Open issues
- HPOBench
- 34
- Awesome-AI-Data-Guided-Projects
- 3
Language
- HPOBench
- Python
- Awesome-AI-Data-Guided-Projects
- -
Adopt for
- HPOBench
- HPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios.
- Awesome-AI-Data-Guided-Projects
- Awesome-AI-Data-Guided-Projects is a curated list featuring projects for building conversational chatbots using large language models and fine-tuning LLMs with LoRA, suitable for portfolio-building in AI.
Persona
- HPOBench
- -
- Awesome-AI-Data-Guided-Projects
- -
Runtime
- HPOBench
- -
- Awesome-AI-Data-Guided-Projects
- -
License
- HPOBench
- HPOBench is open source under the Apache-2.0 license.
- Awesome-AI-Data-Guided-Projects
- GPL-3.0 License allows free use for personal and commercial purposes but requires users to make their modifications available under the same license terms.
Last pushed
- HPOBench
- May 21, 2025
- Awesome-AI-Data-Guided-Projects
- May 5, 2024
Categories
- HPOBench
- Model Training
- Awesome-AI-Data-Guided-Projects
- Developer Tools, LLM Frameworks, Model Training
Trust and health
Days since push
- HPOBench
- 498d
- Awesome-AI-Data-Guided-Projects
- 870d
Open issues (now)
- HPOBench
- 34
- Awesome-AI-Data-Guided-Projects
- 3
Stars delta
- HPOBench
- +3 (30d)
- Awesome-AI-Data-Guided-Projects
- +1 (30d)
Open issues delta
- HPOBench
- 0 (30d)
- Awesome-AI-Data-Guided-Projects
- +1 (30d)
Owner type
- HPOBench
- Organization
- Awesome-AI-Data-Guided-Projects
- User
OSV dependency advisories
- HPOBench
- Published findings
- Awesome-AI-Data-Guided-Projects
- No lockfile (source not queried)
Full report
- HPOBench
- Trust report
- Awesome-AI-Data-Guided-Projects
- Trust report
Choose HPOBench if…
- License: HPOBench is Apache-2.0, Awesome-AI-Data-Guided-Projects is GPL-3.0.
- Requirements: The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step..
- Tags unique to HPOBench: automl, bayesian-optimization, benchmark, hyperparameter-optimization.
- When you are specifically interested in benchmarking hyperparameter optimization problems that include containerized benchmarks to ensure consistency across environments.
When NOT to use HPOBench
- Avoid HPOBench if your project does not require Python or you are looking for a platform that exclusively focuses on the automation of model selection without hyperparameter optimization.
- If you prefer tools with built-in support for multiple programming languages, rather than focusing solely on Python as is the case with HPOBench.
Choose Awesome-AI-Data-Guided-Projects if…
- License: Awesome-AI-Data-Guided-Projects is GPL-3.0, HPOBench is Apache-2.0.
- Tags unique to Awesome-AI-Data-Guided-Projects: ai, computer-vision, datascience, deep-learning.
- Also covers Developer Tools, LLM Frameworks.
- You need guided projects to build conversational chatbot applications.
When NOT to use Awesome-AI-Data-Guided-Projects
- Looking for end-to-end LLM training from scratch; this tool focuses more on fine-tuning and guided projects.
- In search of proprietary AI tools or custom enterprise solutions, as Awesome-AI-Data-Guided-Projects offers open-source project guides.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (automl/HPOBench) · observed Oct 2, 2026
- GitHub forks (automl/HPOBench) · observed Oct 2, 2026
- Last push (automl/HPOBench) · observed May 21, 2025
- License file (Apache-2.0) · observed Oct 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed Sep 23, 2026
- GitHub forks (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed Sep 23, 2026
- Last push (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed May 5, 2024
- License file (GPL-3.0) · observed Sep 23, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: HPOBench 173 · Awesome-AI-Data-Guided-Projects 724 (synced Oct 2, 2026).
Common questions
- What is the difference between HPOBench and Awesome-AI-Data-Guided-Projects?
- HPOBench: A collection of hyperparameter optimization benchmark problems. Awesome-AI-Data-Guided-Projects: A curated list of data science & AI guided projects for portfolio-building. See the comparison table for live GitHub stats and shared categories.
- When should I choose HPOBench over Awesome-AI-Data-Guided-Projects?
- Choose HPOBench over Awesome-AI-Data-Guided-Projects when License: HPOBench is Apache-2.0, Awesome-AI-Data-Guided-Projects is GPL-3.0; Requirements: The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step.; Tags unique to HPOBench: automl, bayesian-optimization, benchmark, hyperparameter-optimization; When you are specifically interested in benchmarking hyperparameter optimization problems that include containerized benchmarks to ensure consistency across environments.
- When should I choose Awesome-AI-Data-Guided-Projects over HPOBench?
- Choose Awesome-AI-Data-Guided-Projects over HPOBench when License: Awesome-AI-Data-Guided-Projects is GPL-3.0, HPOBench is Apache-2.0; Tags unique to Awesome-AI-Data-Guided-Projects: ai, computer-vision, datascience, deep-learning; Also covers Developer Tools, LLM Frameworks; You need guided projects to build conversational chatbot applications.
- When should I avoid HPOBench?
- Avoid HPOBench if your project does not require Python or you are looking for a platform that exclusively focuses on the automation of model selection without hyperparameter optimization. If you prefer tools with built-in support for multiple programming languages, rather than focusing solely on Python as is the case with HPOBench.
- When should I avoid Awesome-AI-Data-Guided-Projects?
- Looking for end-to-end LLM training from scratch; this tool focuses more on fine-tuning and guided projects. In search of proprietary AI tools or custom enterprise solutions, as Awesome-AI-Data-Guided-Projects offers open-source project guides.
- Is HPOBench or Awesome-AI-Data-Guided-Projects more popular on GitHub?
- Awesome-AI-Data-Guided-Projects has more GitHub stars (724 vs 173). Stars measure visibility, not whether either tool fits your constraints.
- Are HPOBench and Awesome-AI-Data-Guided-Projects open source?
- Yes - both are open-source projects on GitHub (HPOBench: Apache-2.0, Awesome-AI-Data-Guided-Projects: GPL-3.0).
- Where can I find alternatives to HPOBench or Awesome-AI-Data-Guided-Projects?
- GraphCanon lists graph-backed alternatives at HPOBench alternatives and Awesome-AI-Data-Guided-Projects alternatives (HPOBench markdown twin, Awesome-AI-Data-Guided-Projects markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, HPOBench or Awesome-AI-Data-Guided-Projects?
- HPOBench: Dormant. Awesome-AI-Data-Guided-Projects: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for HPOBench and Awesome-AI-Data-Guided-Projects?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: HPOBench trust report; Awesome-AI-Data-Guided-Projects trust report.