# yangxudong/deeplearning

深度学习相关的模型训练、评估和预测相关代码

Repository: https://github.com/yangxudong/deeplearning
Canonical: https://ross.abutalabs.com/products/yangxudong-deeplearning
Language: Python
License Family: other
Last push: 2021-07-26T06:01:32+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2963, "days_push": 1864, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1049, forks 378 (observed 2026-08-28T04:03:22.731841+00:00)

## What it is
A collection of deep learning model training, evaluation, and prediction code implemented with TensorFlow's high-level Estimator API, with a focus on CTR prediction models. It emphasizes readability and generality and includes documentation for several model subdirectories.

## Use cases
- train deep learning models with tensorflow estimator
- implement CTR prediction models like ESMM
- build distributed deep learning training pipelines
- learn tensorflow dataset api input pipelines
- text classification with CNN in tensorflow
- feature engineering with tensorflow feature columns

## When to choose
- you work with TensorFlow 1.x Estimator API and want readable reference implementations
- you need CTR/recommendation model examples such as ESMM
- you want to learn distributed training patterns with high-level TensorFlow APIs

## When to avoid
- you use TensorFlow 2.x or PyTorch exclusively
- you need a maintained production library with a license and active releases
- you need modern deep learning tooling outside CTR prediction

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, machine-learning, llm-training
- domain: deep-learning, machine-learning
- platform: python
- tags: tensorflow, ctr-prediction, estimator, recommendation-systems, model-training, recommendation

## Member repositories
- yangxudong/deeplearning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:22.731841+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 2026-08-30T07:00:34.050104+00:00, confidence not recorded.
  - readme: https://github.com/yangxudong/deeplearning (fetched 2026-08-28T04:03:22.731841+00:00, sha 09c1a489ee8c)
- Data as of 2026-08-30T08:39:29.467469+00:00.