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TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials resource

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more. observed · 2026-08-28

github.com/TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials · homepage · Python · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

38/100

  • Activity 12
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3338
  • days_rel: n/a
  • days_push: 532
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

4002 stars · 1625 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated collection of IPython notebook tutorials covering deep learning, artificial intelligence, and machine learning with frameworks like TensorFlow, PyTorch, and Keras. It also spans industry-specific applications such as healthcare, energy, and retail, and is updated regularly.

Use cases

  • learn deep learning with pytorch notebooks
  • find tensorflow tutorials for beginners
  • study machine learning examples in python
  • explore NLP and computer vision tutorials
  • learn keras and scikit-learn through notebooks
  • find AI tutorials for healthcare and energy applications

When to choose

  • you want hands-on notebook-based tutorials across many ML/DL frameworks
  • you need curated links to probabilistic programming and deep learning examples
  • you are exploring industry-specific AI applications

When to avoid

  • you need production-ready code or maintained libraries
  • you want a single coherent course rather than a mixed collection
  • you require a permissively licensed codebase (license is non-standard)

Facets

learning-resource · maturity active

machine-learning deep-learning nlp computer-vision data-science artificial-intelligence machine-learning deep-learning computer-vision tutorials python cross-platform tutorials ipython-notebooks tensorflow pytorch keras curated-list awesome-list natural-language-processing

2 sources

Member repositories

For agents

markdown · JSON · MCP: product_card(name="TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem