23 Classic Machine Learning Project Ideas for Beginners, Intermediate, and Advanced Levels

Machine learning practitioners often seek hands‑on projects to bridge the gap between theory and practice; this article compiles 23 classic project ideas covering beginner, intermediate, and advanced levels, each with a concise description, dataset source, and optional code links.

Beginner Machine Learning Projects

1. Iris Classification – Classify iris species using petal and sepal measurements (Dataset: UCI Iris). 2. Emojify – Build a CNN to map facial expressions to emojis (Code link provided). 3. Loan Prediction – Predict loan eligibility with a linear model (Dataset: Kaggle loan prediction). 4. Housing Price Prediction – Estimate Boston house prices using various features (Dataset: Boston housing). 5. MNIST Digit Classification – Recognize handwritten digits with a CNN (Dataset: MNIST). 6. Stock Price Prediction – Forecast future stock prices from historical data (Dataset: Kaggle two‑sigma). 7. Titanic Survival – Predict passenger survival using the Titanic dataset (Dataset: Kaggle Titanic). 8. Wine Quality Detection – Predict wine quality from chemical properties (Dataset: UCI wine quality). 9. Fake News Detection – Distinguish false from real news articles (Dataset: Google Drive link).

Intermediate Machine Learning Projects

1. Music Genre Classification – Classify audio tracks into genres using spectral features (Code link provided). 2. Bitcoin Price Predictor – Forecast Bitcoin prices using historical market data (Dataset: Kaggle Bitcoin). 3. Uber Data Analysis – Visualize and analyze 4.5 million NYC Uber trips (Dataset: Google Drive). 4. Personality Prediction – Infer Myers‑Briggs types from social media posts (Dataset: Kaggle MBTI). 5. Xbox Game Recommendation – Recommend Xbox games based on user search logs (Dataset: Kaggle). 6. Credit Card Fraud Detection – Detect fraudulent transactions with classification models (Dataset: Google Drive). 7. Barbie & Brain – Give a toy chatbot conversational abilities using ML. 8. Customer Segmentation – Segment customers by demographics and behavior (Dataset: Google Drive).

Advanced Machine Learning Projects

1. Sentiment Analysis – Classify text sentiment as positive, negative, or neutral (Dataset: Stanford). 2. Enron Email Investigation – Analyze the Enron email corpus for insights (Dataset: CMU). 3. Speech Emotion Recognition – Identify speaker emotions from audio clips (Dataset: Google Drive). 4. Illegal Fishing Detection – Detect unlawful fishing activities using satellite and GPS data (Dataset: Global Fishing Watch). 5. Online Grocery Recommendation – Build a collaborative‑filtering system for grocery items. 6. Movie Recommendation System – Create a personalized movie recommender (Dataset: Google Drive). 7. License Plate Recognition – Detect and read vehicle license plates from images (Code link provided).

Source: Compiled from “机器学习算法那些事” and “AI有道”.