Here are 10 beginner-friendly AI and big data projects to help you gain hands-on experience:
1. Sentiment Analysis on Social Media Data
Goal: Analyze public sentiment around a product or event.
Skills: Text preprocessing, Natural Language Processing (NLP).
Tools: Python, Pandas, NLTK/Spacy, and a dataset from Twitter (via APIs like Tweepy).
Big Data Aspect: Work with large social media datasets.
2. Movie Recommendation System
Goal: Build a recommendation engine for movies.
Skills: Collaborative filtering, content-based filtering.
Tools: Python, Scikit-learn, Surprise library.
Big Data Aspect: Use large movie datasets like MovieLens.
3. Customer Segmentation
Goal: Segment customers based on purchasing behavior.
Skills: K-means clustering, data visualization.
Tools: Python, NumPy, Matplotlib, and Scikit-learn.
Big Data Aspect: Use datasets like Kaggle’s "Online Retail Dataset."
4. Predictive Maintenance
Goal: Predict equipment failure using IoT sensor data.
Skills: Time-series analysis, supervised learning.
Tools: Python, TensorFlow/PyTorch, Pandas.
Big Data Aspect: Handle IoT sensor datasets.
5. Fraud Detection
Goal: Identify fraudulent transactions in financial data.
Skills: Anomaly detection, supervised learning.
Tools: Python, Scikit-learn, and a financial fraud dataset.
Big Data Aspect: Work with large transaction datasets.
6. AI Chatbot with FAQs
Goal: Build a chatbot that answers customer FAQs.
Skills: NLP, retrieval-based systems.
Tools: Python, Rasa/Dialogflow, Hugging Face Transformers.
Big Data Aspect: Train the chatbot on a dataset of customer queries and answers.
7. Traffic Prediction System
Goal: Predict traffic congestion in a city using past data.
Skills: Time-series forecasting, regression models.
Tools: Python, TensorFlow/PyTorch, GeoPandas.
Big Data Aspect: Work with traffic sensor datasets or Google Maps API data.
8. Healthcare Data Analysis
Goal: Analyze patient records to predict diseases.
Skills: Logistic regression, data preprocessing.
Tools: Python, TensorFlow, Scikit-learn.
Big Data Aspect: Work with healthcare datasets like MIMIC-III.
9. Image Recognition for E-commerce
Goal: Build an AI model to classify product images.
Skills: Convolutional Neural Networks (CNNs), image preprocessing.
Tools: Python, TensorFlow/Keras.
Big Data Aspect: Work with datasets like Amazon’s product images dataset.
10. Housing Price Prediction
Goal: Predict house prices based on features like location, size, and age.
Skills: Regression models, feature engineering.
Tools: Python, Scikit-learn, and datasets like the Kaggle "House Prices" dataset.
Big Data Aspect: Handle large datasets of real estate properties.
Let me know if you'd like more details about any of these projects!
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Credit card fraud detection
Recommendation system
Building chatbots
Customer churn analysis
Identify sentiments
Image denoising
Sentiment analysis
Traffic control using Big Data
Data visualization
Exploratory data analysis
Face recognition system
Health status prediction
MapReduce in Big Data
Market basket analysis
Movie recommendation system
Search engine
Taxi demand prediction
Tourist behavior analysis
Anomaly detection in cloud servers
Stock price prediction
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