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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