machine learning projects with source code

  1. Decentralized Voting System Using Blockchain
    • Integrates blockchain technology with machine learning to enhance the security and transparency of electronic voting systems.
    • Aims to address challenges related to fraud and data tampering in electoral processes.
  2. UPI Fraud Detection Using Machine Learning
    • Employs machine learning algorithms to detect and prevent fraudulent activities in Unified Payments Interface (UPI) transactions.
    • Analyzes transaction patterns to identify anomalies indicative of fraud.
  3. DeepFake Face Detection Using Machine Learning
    • Develops a system capable of identifying manipulated facial images and videos generated by deepfake technologies.
    • Utilizes convolutional neural networks (CNNs) to detect subtle inconsistencies in facial features.
  4. Employee Layoff Prediction Using Recurrent Neural Network
    • Predicts potential employee layoffs by analyzing historical workforce data through recurrent neural networks (RNNs).
    • Assists organizations in proactive human resource planning.
  5. Secure Banking Transactions Using Blockchain Technology
    • Combines blockchain and machine learning to secure banking transactions, ensuring data integrity and reducing fraud.
    • Implements smart contracts for automated transaction verification.
  6. AI-Based Multi-Disease Detection Using Machine Learning
    • Creates a diagnostic tool that can identify multiple diseases simultaneously using patient data and machine learning models.
    • Enhances early detection and treatment planning in healthcare.
  7. Fake Job Post Detection Using Machine Learning
    • Detects fraudulent job postings on online platforms by analyzing textual content and posting patterns.
    • Protects job seekers from scams and misinformation.
  8. AI-Based Learning Assistant Using Machine Learning
    • Develops an intelligent tutoring system that adapts to individual learning styles and paces using machine learning algorithms.
    • Enhances personalized education experiences.
  9. House Price Prediction Using Machine Learning
    • Predicts real estate prices based on various features such as location, size, and market trends using regression models.
    • Assists buyers and sellers in making informed decisions.
  10. Agricultural Crop Recommendations Based on Productivity and Season
    • Provides farmers with crop suggestions tailored to seasonal conditions and soil productivity using machine learning.
    • Aims to optimize agricultural yield and resource utilization.

Additional Machine Learning Project with Source Code

  • Analyzes Instagram post metrics to predict and enhance content reach.
  • Utilizes web scraping and ML algorithms to predict laptop prices based on specifications

  • Predicts video game sales by analyzing historical sales data and market trends.
  • Employs ML models to predict the likelihood of heart disease based on patient data.

  • Predicts customer food ordering patterns to optimize inventory and reduce waste.
  • Develops a system to trace contacts of infected individuals using ML for effective disease control.
  • Detects sarcasm in textual data, enhancing sentiment analysis accuracy.
  • Predicts medical insurance costs based on individual health profiles and demographics.
  • Segments credit card customers into distinct groups for targeted marketing strategies.
  • Analyzes real-time data streams to determine public sentiment on various topics.

  • Healthcare (e.g., disease prediction)
  • Finance (e.g., fraud detection)
  • E-commerce (e.g., recommendation systems)
  • Natural Language Processing (e.g., sentiment analysis)
  • Computer Vision (e.g., image classification, object detection)

1. What are the best machine learning projects with source code for beginners?

Beginner-friendly ML projects include simple tasks like Iris flower classification, spam
detection, and house price prediction. These projects come with Python code and
easy-to-follow instructions, ideal for students or self-learners.

2. Do you provide machine learning projects for final year students with source code?

Yes, we offer a wide range of IEEE-based final year machine learning projects complete with
abstracts, Python source code, datasets, and implementation support.

3. Are the machine learning projects available in Python?

Most of our machine learning projects are developed using Python, including libraries like
Scikit-learn, TensorFlow, and PyTorch. Each project includes Python code, dataset, and
setup instructions.

4. What are some real-world machine learning projects with source code?

We offer real-world ML projects in domains like healthcare diagnostics, stock prediction,
customer churn analysis, sentiment classification, and more all with ready-to-use source
code.

5. Do your machine learning projects come with documentation and explanation?

Absolutely. Every project includes source code, project report, and step-by-step
documentation to help you understand the ML workflow from data preprocessing to model
evaluation.

6. How do I choose the best machine learning project for my academic requirements?

Choose based on your skill level, domain interest, and time constraints. Our categorized
project list includes beginner, intermediate, and advanced ML projects to make selection
easier
Machine Learning Projects with Source Code 2026