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  1. Home
  2. Repositories
  3. tangyudi
  4. Ai-Learn
UnknownNiche visibilityStale activityNo linked package signalPartial snapshot

tangyudi/Ai-Learn

Rank not captured·Top 100·All-time stars·◐Cached ranking snapshot·Updated Aug 15, 2026

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

Compare closest alternativesOpen GitHub

First read

Useful directional context, not a final verdict yet

tangyudi/Ai-Learn is better read as a directional signal than a clean recommendation. Keep the snapshot conservative and validate source activity, package reality, and close alternatives before committing to it.

Visible

13.3K public stars in the current GitStar snapshot.

Needs a narrower context read

Active

Last commit Jun 2, 2024.

Stale activity

Adopted

Treat stars as discovery context until a linked package appears.

No linked package mapping

Confidence

One or more key signals are partial, so GitStar keeps the interpretation conservative.

Partial snapshot

Snapshot facts

  • 13.3K stars
  • 2.7K forks
  • Last commit Jun 2, 2024
  • Package usage not mapped yet

Compare lens

ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code and academic/awesome-datascience are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.

Signal trail

Trajectory

Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.

Daily momentum
Recent momentum is not captured
Weekly momentum
Recent momentum is not captured
Monthly momentum
Recent momentum is not captured
Last commit
Jun 2, 2024

Package reality

No linked npm or PyPI package is mapped for this repository yet, so the page leans more heavily on GitHub-visible popularity and should be read more conservatively.

No linked package signal is expected for this project type, so the read leans more heavily on repository-level public signals.

Hype vs Reality
Insufficient Package Data
Package mapping
No linked package yet
Cross-links
Standalone repo read

Validation note

GitStar can summarize public signals for tangyudi/Ai-Learn, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.

algorithmartificial-intelligencecaffecvdata-analysisdata-miningdata-sciencedeep-learningkerasmachine-learningmathematicsmatplotlibnlpnumpypandaspythonpytorchseaborntensorflowtensorflow2
🐙Polyglot
🛡️ Editorial Context

GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.

Why this rank

This repo is here because it still carries strong GitHub attention.

📈 Momentum & Adoption Signals
Approximate star trajectory

Reconstructed from current stars and cached daily/weekly/monthly deltas.

Now: 13.3K
30d ago7d ago1d agoNow
Daily momentum
No signal
Weekly momentum
No signal
Monthly momentum
No signal
Signal mix (log-scaled for readability)
Current stars13.3K
🧭 Hype vs Reality
Insufficient Package Data

GitStar can see repository momentum, but it does not have a reliable linked package signal yet.

Treat stars and recent movement as discovery context only until npm or PyPI usage is available.

Status
Insufficient Package Data
Package footprint
No linked npm or PyPI usage signal
Method note
This label appears when GitStar cannot find strong enough package telemetry to compare attention against adoption. Compare it against other Unknown repos before treating stars as a moat.
📐 Read the Hype vs Reality heuristic
Related alternative

ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

Shares the learning category footprint with tangyudi/Ai-Learn, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

academic/awesome-datascience

Shares the learning category footprint with tangyudi/Ai-Learn, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

lukasmasuch/best-of-ml-python

Shares the learning category footprint with tangyudi/Ai-Learn, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

dair-ai/ML-YouTube-Courses

Shares the learning category footprint with tangyudi/Ai-Learn, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Research links

Cross-links

Compare against related repos

GitStar picked 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code + awesome-datascience as the closest next comparison from the related repository set.

Open compare presetCompare with 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-codeCompare with awesome-datascience
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Wider nearby ecosystem

Compare with 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-codeCompare with awesome-datascience
Unknown
36.3K stars
ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

Unknown
29.8K stars
academic/awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

Unknown
23.7K stars
lukasmasuch/best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Unknown
17.4K stars
dair-ai/ML-YouTube-Courses

📺 Discover the latest machine learning / AI courses on YouTube.

Unknown
16.6K stars
bharathgs/Awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Python
67K stars
scikit-learn/scikit-learn

scikit-learn: machine learning in Python

Next step after the validation read

Move into a compare preset, organization view, or the heuristic notes once this first fold tells you whether the repo looks visible, active, adopted, and credible enough to keep researching.
Compare the closest alternativesRead the heuristic

Learn and methodology

Keep trust-building context reachable, but behind the first data read instead of ahead of it.
GuideMethodologyArticlesWeekly Digest

About This Page

This page provides a quick overview of tangyudi/Ai-Learn based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.

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