# krishnaik06/Complete-Data-Science-With-Machine-Learning-And-NLP-2024

Repository: https://github.com/krishnaik06/Complete-Data-Science-With-Machine-Learning-And-NLP-2024
Canonical: https://ross.abutalabs.com/products/complete-data-science-with-machine-learning-and-nlp-2024
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2024-07-10T18:20:22+00:00

## Health v2 (maintenance only)
Score: 24/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 58
- inputs: {"age_days": 822, "days_push": 784, "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 2856, forks 3336 (observed 2026-08-28T04:07:25.743658+00:00)

## What it is
A companion repository for Krish Naik's Udemy course on complete data science, machine learning, NLP, and MLOps with end-to-end projects. It contains Jupyter Notebook course materials covering supervised/unsupervised learning, deep learning, NLP, and deployment tools like MLflow, BentoML, DVC, and GitHub Actions.

## Use cases
- learn machine learning from scratch
- study NLP techniques with hands-on projects
- practice end-to-end ML project deployment
- learn MLOps tools like MLflow and DVC
- prepare for a data science career with structured course material
- understand CI/CD pipelines for ML projects

## When to choose
- you want a structured, beginner-friendly curriculum covering ML, NLP, and MLOps
- you prefer learning through end-to-end practical projects
- you are following Krish Naik's Udemy course and need the code materials

## When to avoid
- you need production-ready ML software or libraries rather than educational notebooks
- you want a reference implementation to deploy directly
- you need documentation or tooling rather than tutorials

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, nlp, deep-learning, etl, ci-cd
- domain: machine-learning, data-science, tutorials, education
- platform: python
- tags: udemy-course, mlops, jupyter-notebooks, end-to-end-projects, krish-naik, course-materials, natural-language-processing

## Member repositories
- krishnaik06/Complete-Data-Science-With-Machine-Learning-And-NLP-2024 (main) score 24

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:25.743658+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 2026-08-30T07:36:31.110108+00:00, confidence not recorded.
  - readme: https://github.com/krishnaik06/Complete-Data-Science-With-Machine-Learning-And-NLP-2024 (fetched 2026-08-28T04:07:25.743658+00:00, sha 3ac221751449)
- Data as of 2026-08-30T08:39:29.467469+00:00.