# GauravBh1010tt/DeepLearn

Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.

Repository: https://github.com/GauravBh1010tt/DeepLearn
Canonical: https://ross.abutalabs.com/products/deeplearn
Language: Python
License: MIT
License Family: permissive
Topics: deep-learning, nlp, computer-vision, audio-processing
Last push: 2022-12-04T23:59:48+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3392, "days_push": 1368, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1847, forks 349 (observed 2026-08-28T04:05:43.514120+00:00)

## What it is
A collection of Python implementations of deep learning research papers covering NLP, computer vision, and machine learning topics using Keras, TensorFlow, and Scikit-learn. It serves as an educational reference for reproducing models like CorrNet, ABCNN, Siamese networks, and neural tensor networks.

## Use cases
- learn how to implement deep learning research papers in keras
- study sentence similarity models like MaLSTM
- understand attention-based CNNs for sentence pair matching
- reproduce community question answering models from papers
- explore correlation neural network implementations
- find reference code for neural tensor networks for knowledge base completion

## When to choose
- you want readable reference implementations of classic deep learning NLP and CV papers
- you are studying paper reproduction techniques with Keras and TensorFlow
- you need example code for sentence matching, ranking, or representation learning models

## When to avoid
- you need a production-ready maintained library with API guarantees
- you want modern PyTorch implementations or transformer-based models
- you need actively updated code with recent dependency support

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, nlp, machine-learning, computer-vision
- domain: deep-learning, computer-vision, tutorials
- platform: python
- tags: research-papers, keras, tensorflow, scikit-learn, paper-implementations, sentence-similarity, question-answering, natural-language-processing

## Member repositories
- GauravBh1010tt/DeepLearn (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:43.514120+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 2026-08-30T03:17:49.986376+00:00, confidence not recorded.
  - readme: https://github.com/GauravBh1010tt/DeepLearn (fetched 2026-08-28T04:05:43.514120+00:00, sha a5159236feee)
- Data as of 2026-08-30T08:39:29.467469+00:00.