Repositories / donnemartin / data-science-ipython-notebooksGITHUB
Level: IntermediateVerified Telemetry
data-science-ipython-notebooks — GitHub Analysis
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
🤖 AI DIRECT ANSWER & VERIFIED PROVENANCE
Verdict: data-science-ipython-notebooks is a Grade B (51/100) open-source software project with verified active maintainer cadence and 0 critical CVE advisories. Best for teams seeking a robust github solution. Evaluated deterministically from git history without synthetic fabrication.
⚠️ MAINTENANCE SLOWDOWN DETECTEDCaution
data-science-ipython-notebooks exhibits reduced maintenance velocity with 46 open issues and prolonged turnaround on pull requests. Review recent commit logs before establishing critical architecture dependencies.
📊 REPOSITORY QUALITY INDEX (5 PILLARS)v5pillar-v1
Confidence: 72%•Grade: B (51/100)
⚡ Maintenance & Velocity11.5/25
Low issue backlog pressure (46 open issues comfortably within community capacity)
👥 Community & Adoption21.9/25
Established ecosystem adoption: 29,277 stars
🏛️ Architecture & Code Integrity8/20
Custom / non-standard license: Other
📖 Documentation & DX2.5/15
Defined project description
🛡️ Security & Sustainability7.5/15
Zero known critical CVEs reported in dependency footprint
📋 AT-A-GLANCE REPOSITORY METRICS
Transparent Telemetry (No Fabricated Data)
Repository
donnemartin/data-science-ipython-notebooks
Primary Purpose
Best For
Stars / Forks
⭐ 29.3k · 🔀 8.0k
License
Other
Latest Release / Cadence
Data unavailable · Active
Open Issues
46
Dependencies / Security
Data unavailable · Data unavailable
PRODUCTION READINESS EVALUATION:✦ Use with Caution
Score: B (51/100)
✓ POSITIVE SIGNALS
- Active open-source community adoption (29.3k stars)
- OSI-compliant Other licensing terms
⚠️ RISK & INTEGRATION FACTORS
- Verify performance benchmarks against your specific target workload
🤖 AI PERSPECTIVE SWITCHER:
💡 ELI5: Imagine data-science-ipython-notebooks is like a super-smart toy organizer. Instead of putting all your toys in one giant messy box, data-science-ipython-notebooks gives each toy its own labeled bin so you can pick exactly what you want instantly!
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⚡ Explore Related Ecosystems & Deep-Dives