# shsarv/Machine-Learning-Projects

This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to practical scenarios, demonstrating proficiency in machine learning techniques and tools.

Repository: https://github.com/shsarv/Machine-Learning-Projects
Canonical: https://ross.abutalabs.com/products/machine-learning-projects
Homepage: https://shsarv.github.io/Machine-Learning-Projects/
Language: Jupyter Notebook
License Family: other
Topics: machine-learning-projects, projects, ml-project, python-project, machinelearning-python, machine-learning-project, deep-learning-project, deep-learning-projects, nlp-project, nlp-projects, opencv-project, opencv-projects
Last push: 2026-07-17T17:50:04+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 35, longevity 100
- inputs: {"age_days": 2119, "days_push": 47, "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 1833, forks 579 (observed 2026-08-28T04:05:42.389579+00:00)

## What it is
A curated collection of 26 end-to-end machine learning projects in Jupyter Notebooks covering deep learning, NLP, computer vision, healthcare AI, and time series forecasting. Several projects are deployed as web or GUI applications, making it a practical learning portfolio.

## Use cases
- learn machine learning through hands-on projects
- find example projects for deep learning and NLP
- build a machine learning portfolio
- study end-to-end ML project implementations
- learn OpenCV computer vision projects
- explore healthcare AI prediction models

## When to choose
- you want complete, runnable example projects across many ML domains
- you are a student or beginner building practical ML skills
- you need reference implementations for CV, NLP, or time series tasks

## When to avoid
- you need a production-ready library or framework with an API
- you require licensed, maintained software for commercial use (no license is provided)
- you need a single cohesive tool rather than a set of independent notebooks

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, nlp, computer-vision, chatbot, data-science
- domain: machine-learning, deep-learning, computer-vision, data-science, healthcare, tutorials
- platform: python, cross-platform
- tags: jupyter-notebooks, portfolio-projects, opencv, time-series-forecasting, beginner-friendly, end-to-end-projects, natural-language-processing

## Member repositories
- shsarv/Machine-Learning-Projects (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:42.389579+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 2026-08-30T03:18:38.753155+00:00, confidence not recorded.
  - readme: https://github.com/shsarv/Machine-Learning-Projects (fetched 2026-08-28T04:05:42.389579+00:00, sha f7f70c59bdaa)
  - homepage: https://shsarv.github.io/Machine-Learning-Projects/ (fetched 2026-08-29T10:58:10.253191+00:00, sha b7a59e8c15bd)
- Data as of 2026-08-30T08:39:29.467469+00:00.