Machine Learning Projects
Here’s a categorized list of machine learning project ideas—from beginner to advanced level—across various domains. These will help you build real-world experience and enhance your resume or portfolio.
🔹 Beginner Projects
- Iris Flower Classification
- Use the classic Iris dataset to predict flower species using classification algorithms like k-NN or Logistic Regression.
- Titanic Survival Prediction
- Use passenger data to predict who survived the Titanic disaster (Kaggle dataset).
- House Price Prediction
- Predict house prices using features like area, location, number of rooms, etc. (Linear Regression).
- MNIST Digit Classification
- Use deep learning (CNNs) to classify handwritten digits.
- Movie Recommendation System
- Build a collaborative filtering-based recommender using user ratings (e.g., MovieLens dataset).
🔹 Intermediate Projects
- Email Spam Detection
- Build a spam classifier using Natural Language Processing (NLP) techniques like TF-IDF and Naive Bayes.
- Credit Card Fraud Detection
- Use anomaly detection or classification to identify fraudulent transactions.
- Customer Churn Prediction
- Predict whether a customer will leave a subscription service based on usage data.
- Fake News Detection
- Classify whether a news article is fake or real using NLP and logistic regression/SVM.
- Loan Approval Prediction
- Classify whether a loan should be approved based on applicant details.
- Facial Expression Recognition
- Use CNNs to classify facial emotions (happy, sad, angry, etc.).
- Stock Price Prediction
- Apply LSTM (Recurrent Neural Networks) to forecast stock prices using time-series data.
🔹 Advanced Projects
- Self-Driving Car Simulation
- Use deep learning with a simulator (e.g., Carla) to create perception and control systems.
- Chatbot with NLP & Transformers
- Create a chatbot using Transformer models like BERT or GPT.
- Object Detection with YOLO or SSD
- Detect and label objects in images using real-time deep learning object detection models.
- Machine Translation
- Build a neural machine translation system using seq2seq architecture.
- Music Genre Classification
- Classify songs into genres using audio features and spectrograms (Librosa, CNNs).
- Medical Image Diagnosis
- Diagnose conditions like pneumonia or COVID-19 using X-ray images and CNNs.
- GANs for Image Generation
- Use Generative Adversarial Networks to create new images (e.g., faces, artwork).
- Autonomous Drone Navigation
- Use RL (Reinforcement Learning) to train drones to navigate obstacles.
🔹 NLP-Focused Projects
- Sentiment Analysis on Twitter Data
- Scrape tweets and classify sentiment (positive/negative/neutral).
- Text Summarization
- Use extractive or abstractive methods (e.g., BART) to summarize long texts.
- Resume Parser
- Build a tool to extract data from resumes and categorize candidate skills.
- Named Entity Recognition (NER)
- Identify entities like names, places, and dates in text using SpaCy or HuggingFace models.
- Speech-to-Text Transcription
- Use libraries like DeepSpeech or Whisper to convert spoken language to text.
🔹 Domain-Specific Ideas
- Healthcare: Disease prediction, drug discovery using ML, patient risk scoring.
- Finance: Loan default prediction, algorithmic trading strategies, portfolio optimization.
- Retail: Inventory demand forecasting, customer segmentation, pricing optimization.
- Cybersecurity: Intrusion detection systems, phishing email detection, malware classification.
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