Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This repository is a curated collection of hands-on data science projects tailored for beginners. Whether you're just starting your journey in data science or looking to strengthen your skills, these projects provide a practical and interactive way to apply your knowledge.
| Date | Stars |
|---|---|
| 2026-07-24 | 2926 |
| 2026-07-25 | 2933 |
| 2026-07-28 | 2933 |
| 2026-07-30 | 2933 |
| 2026-08-09 | 2998 |
| 2026-08-17 | 3032 |
| 2026-08-18 | 3038 |
| 2026-08-19 | 3046 |
| 2026-08-20 | 3051 |
| 2026-08-21 | 3054 |
| 2026-08-22 | 3064 |
| 2026-08-23 | 3067 |
| 2026-08-24 | 3073 |
| 2026-08-25 | 3076 |
| 2026-08-26 | 3083 |
| 2026-08-27 | 3089 |
| 2026-08-28 | 3090 |
| 2026-08-29 | 3095 |
| 2026-08-30 | 3102 |
| 2026-08-31 | 3105 |
| 2026-09-01 | 3112 |
| 2026-09-02 | 3113 |
| 2026-09-03 | 3116 |
| 2026-09-04 | 3121 |
| 2026-09-05 | 3123 |
| 2026-09-06 | 3127 |
| 2026-09-07 | 3134 |
| 2026-09-08 | 3138 |
| 2026-09-09 | 3140 |
| 2026-09-10 | 3144 |
| 2026-09-11 | 3148 |
| 2026-09-12 | 3147 |
| 2026-09-13 | 3148 |
| 2026-09-14 | 3150 |
| 2026-09-15 | 3158 |
| 2026-09-16 | 3159 |
| 2026-09-17 | 3163 |
| 2026-09-18 | 3166 |
| 2026-09-19 | 3168 |
| 2026-09-20 | 3174 |
Today
+6 stars today
This week
+26 stars this week
This month
+120 stars this month
Momentum
35.0
growth rate 0.83%/day
<h1 align="center">Beginner Level Data Science Projects</h1> <p align="center"> <img src="assets/data-science.png" alt="Project Overview" width="150"> </p> <p align="center"> <a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="MIT License"></a> <a href="https://github.com/tkarim45/Beginner-Data-Science-Projects/stargazers"><img src="https://img.shields.io/github/stars/tkarim45/Beginner-Data-Science-Projects" alt="Stars"></a> <a href="https://github.com/tkarim45/Beginner-Data-Science-Projects/network/members"><img src="https://img.shields.io/github/forks/tkarim45/Beginner-Data-Science-Projects" alt="Forks"></a> <a href="https://github.com/tkarim45/Beginner-Data-Science-Projects/issues"><img src="https://img.shields.io/github/issues/tkarim45/Beginner-Data-Science-Projects" alt="Issues"></a> <a href="CONTRIBUTING.md"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg" alt="PRs Welcome"></a> </p> <p align="center"> A curated collection of beginner-friendly data science projects with real datasets, clear explanations, and working code. Learn by building. </p> --- ## Table of Contents - [Why This Repo?](#why-this-repo) - [Categories](#categories) - [Learning Path](#learning-path) - [All Projects](#all-projects) - [Getting Started](#getting-started) - [Contributing](#contributing) - [License](#license) ## Why This Repo? This repository is designed for **anyone getting started with data science** -- students, career switchers, and self-learners. Each project is a standalone Jupyter notebook that you can clone and run immediately. You will learn: - **Data Cleaning and Preprocessing** -- preparing real-world messy data - **Exploratory Data Analysis** -- visualizations and statistical insights - **Machine Learning** -- classification, regression, and anomaly detection - **Deep Learning** -- CNNs, transfer learning, and NLP models - **Computer Vision** -- detection, recognition, and pose estimation ## Categories Projects are grouped into category folders, each with its own README listing every project in it: - [Classification](Classification/README.md) (19) - [Regression](Regression/README.md) (16) - [Time Series](Time%20Series/README.md) (6) - [NLP](NLP/README.md) (20) - [Clustering](Clustering/README.md) (4) - [Recommendation Systems](Recommendation%20Systems/README.md) (5) - [Anomaly Detection](Anomaly%20Detection/README.md) (2) - [EDA Visualization](EDA%20Visualization/README.md) (10) - [Miscellaneous Applied](Miscellaneous%20Applied/README.md) (10) - [Computer Vision](Computer%20Vision/README.md) (22) - [Robotics](Robotics/README.md) (1) ## Learning Path Start from the top and work your way down. Projects are ordered by difficulty within each level. ### Level 1 -- Fundamentals Get comfortable with pandas, sklearn, and basic ML workflows. | # | Project | What You'll Learn | Category | |---|---------|-------------------|----------| | 1 | [Titanic Survival Prediction](Classification/Titanic%20Survival%20Prediction) | EDA, data cleaning, feature engineering, 7 classifiers, GridSearchCV | Classification | | 2 | [Iris Flower Classification](Classification/Iris%20Flower%20Classification) | Multi-class classification on the classic iris measurements, data loading | Classification | | 3 | [Customer Churn](Classification/Customer%20Churn) | Logistic regression from scratch, prediction on new data | Classification | | 4 | [Heart Failure Prediction](Classification/Heart%20Failure%20Prediction) | Feature analysis, multiple classifiers, model evaluation | Classification | | 5 | [Rental Prices of AirBnb](Regression/Rental%20Prices%20of%20AirBnb) | Linear regression, outlier analysis, label encoding | Regression | ### Level 2 -- Text and NLP Learn to work with text data, preprocessing pipelines, and NLP techniques. | # | Project | What You'll Learn | Category | |---|---------|-------------------|----------| | 6 | [Message Spam Filtering](NLP/Message%20Spam%20Filtering)
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ARUNAGIRINATHAN_K · Technology Innovation Hub · India
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ff7545ac075bb906, topic:deep-learning, topic:neural-network