# https-deeplearning-ai/tensorflow-1-public

Repository: https://github.com/https-deeplearning-ai/tensorflow-1-public
Canonical: https://ross.abutalabs.com/products/tensorflow-1-public
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Last push: 2024-11-20T14:53:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1895, "days_push": 651, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2611, forks 2687 (observed 2026-08-28T04:07:04.360375+00:00)

## What it is
The public repository of assignments and ungraded labs for the DeepLearning.AI TensorFlow Developer Professional Certificate, organized course-by-course and week-by-week as Jupyter notebooks. It covers neural network fundamentals, CNNs for computer vision, NLP with TensorFlow, and time series forecasting.

## Use cases
- learn tensorflow for deep learning
- practice building neural networks with jupyter notebooks
- course assignments for cnn image classification
- learn nlp with tensorflow
- time series forecasting with tensorflow exercises
- prepare for the tensorflow developer certificate

## When to choose
- you are enrolled in or following the DeepLearning.AI TensorFlow Developer certificate on Coursera
- you want hands-on notebook-based exercises covering CNNs, NLP, and time series in TensorFlow
- you prefer structured, week-by-week guided labs

## When to avoid
- you need a production TensorFlow library or tool rather than educational material
- you want a framework-agnostic or PyTorch-based deep learning course
- you need up-to-date TensorFlow 2.x APIs beyond what the notebooks use

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, nlp, computer-vision
- domain: deep-learning, machine-learning, computer-vision, education, tutorials
- platform: python, cross-platform
- tags: tensorflow, jupyter-notebooks, coursera, course-assignments, neural-networks, cnn, transfer-learning, time-series, deeplearning-ai, natural-language-processing

## Member repositories
- https-deeplearning-ai/tensorflow-1-public (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:04.360375+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:20:51.987498+00:00, confidence not recorded.
  - readme: https://github.com/https-deeplearning-ai/tensorflow-1-public (fetched 2026-08-28T04:07:04.360375+00:00, sha f9636f33a87a)
- Data as of 2026-08-30T08:39:29.467469+00:00.