Are you a beginner looking to dive into the exciting world of machine learning? Building projects is a great way to apply your knowledge, gain hands-on experience, and boost your skills. In this article, we will explore the top 25 machine learning projects for beginners in 2024.
- Predicting Boston Housing Prices: Develop a model to predict housing prices based on features like crime rate, number of rooms, and more.
- Sentiment Analysis: Build a sentiment analysis model to classify text as positive, negative, or neutral.
- Image Classification: Create a model that can classify images into different categories, such as cats and dogs.
- Spam Email Detection: Develop a model to identify spam emails and filter them out.
- Customer Churn Prediction: Build a model to predict customer churn for a business based on historical data.
- Movie Recommendation System: Create a recommendation system that suggests movies to users based on their preferences.
- Credit Card Fraud Detection: Develop a model to detect fraudulent credit card transactions.
- Handwritten Digit Recognition: Build a model that can recognize handwritten digits.
- Stock Price Prediction: Create a model to predict stock prices based on historical data.
- Fake News Detection: Develop a model to identify fake news articles.
- Face Recognition: Build a model that can recognize faces in images or videos.
- Predicting Loan Default: Create a model to predict the likelihood of loan default based on various factors.
- Object Detection: Develop a model that can detect and classify objects in images or videos.
- Customer Segmentation: Build a model to segment customers based on their behavior and characteristics.
- Disease Diagnosis: Create a model to diagnose diseases based on symptoms and medical data.
- Predicting Employee Attrition: Develop a model to predict employee attrition for a company.
- Anomaly Detection: Build a model to detect anomalies or outliers in data.
- Recommendation System for E-commerce: Create a recommendation system for an e-commerce platform to suggest products to users.
- Predicting Air Quality: Develop a model to predict air quality based on various environmental factors.
- Credit Risk Assessment: Build a model to assess the credit risk of borrowers.
- Customer Lifetime Value Prediction: Create a model to predict the lifetime value of customers for a business.
- Predicting Customer Purchase Behavior: Develop a model to predict customer purchase behavior and preferences.
- Predicting Hospital Readmission: Build a model to predict the likelihood of hospital readmission for patients.
- Predicting Loan Approval: Create a model to predict the likelihood of loan approval based on applicant data.
- Predicting Website Traffic: Develop a model to predict website traffic based on historical data.
