AI / ML / Data Science Projects

AI-Based Projects

1. Face Recognition Attendance System
Build an AI model that automatically marks attendance based on facial recognition.
Technologies: OpenCV, Dlib, Face Recognition

2. Personalized Recommendation System
Create a recommendation engine (e.g., for movies, products, etc.) based on user behavior.
Technologies: Collaborative Filtering, Content-Based Filtering, TensorFlow

3. Chatbot for Customer Support
Develop an AI chatbot to answer common questions in a customer service environment.
Technologies: NLP, Rasa, TensorFlow

4. Nepali Language Sentiment Analysis
Analyze the sentiment of Nepali text from social media, reviews, or news articles.
Technologies: NLP, BERT, Transformers

5. AI-based Virtual Assistant
Create a voice-controlled assistant that can answer questions, set reminders, etc.
Technologies: Speech Recognition, NLP, Google Assistant API

6. AI Medical Diagnosis System
Develop a system to diagnose diseases based on patient data (e.g., diabetes, heart disease).
Technologies: Logistic Regression, Neural Networks, Random Forests

7. Image Captioning with Deep Learning
Build a model that generates captions for images using a combination of CNNs and RNNs.
Technologies: CNN, RNN, LSTM, TensorFlow

8. Voice-Based Emotion Recognition
Detect emotions (happy, sad, angry, etc.) from audio or voice input.
Technologies: Audio Processing, Neural Networks, Deep Learning

9. AI-Based Resume Screening System
Automate the process of screening resumes based on job descriptions and requirements.
Technologies: NLP, Text Classification, TensorFlow

10. Text Summarization Model
Build an AI model to summarize long articles or documents.
Technologies: NLP, Transformers, BERT, GPT-3

Machine Learning Projects 

1. Customer Churn Prediction
Predict whether a customer will leave or stay based on behavioral data.
Technologies: Random Forests, XGBoost, Logistic Regression

2. Loan Default Prediction
Predict whether a borrower will default on a loan using financial and demographic data.
Technologies: SVM, Decision Trees, K-Nearest Neighbors (KNN)

3. Stock Market Prediction
Predict stock prices based on historical data and technical indicators.
Technologies: Time Series Analysis, LSTM, ARIMA, Scikit-learn

4. Weather Forecasting Model
Build a model to predict weather conditions based on historical weather data.
Technologies: Regression, Time Series, Neural Networks

5. Fraud Detection in Transactions
Detect fraudulent transactions in financial datasets.
Technologies: Random Forest, Isolation Forest, Anomaly Detection

6. Credit Score Prediction
Predict a person’s credit score based on their financial data and transaction history.
Technologies: Logistic Regression, Neural Networks, Random Forests

7. Email Spam Classification
Create a model that classifies emails as spam or not spam.
Technologies: Naive Bayes, SVM, Logistic Regression

8. Image Classification System

Build a machine learning model to classify images into categories (e.g., cats vs. dogs).
Technologies: CNNs, Keras/TensorFlow

9. Handwriting Recognition System
Recognize handwritten characters or digits (e.g., using the MNIST dataset).
Technologies: CNN, Deep Learning, TensorFlow 

10. Predictive Maintenance System
Predict when industrial equipment is likely to fail, based on sensor data.
Technologies: Random Forests, Neural Networks, Time Series Analysis

Data Science Projects

1. Sales Forecasting
Predict future sales of a product based on historical sales data.
Technologies: Time Series Forecasting, ARIMA, XGBoost

2. Customer Segmentation
Use clustering techniques to segment customers into different groups based on purchasing behavior.
Technologies: K-Means, DBSCAN, Hierarchical Clustering

3. Product Price Optimization
Create a model that determines the best price for a product based on market conditions.
Technologies: Regression, Optimization Algorithms, Scikit-learn

4. Social Media Analytics
Analyze data from social media platforms to gather insights about trends, public opinion, etc.
Technologies: NLP, Text Mining, Sentiment Analysis, Pandas

5. Traffic Prediction Model
Predict traffic congestion in cities based on historical traffic data.
Technologies: Time Series Analysis, Regression, Machine Learning

6. Sports Performance Prediction
Predict the performance of athletes or teams based on historical performance data.
Technologies: Regression, Neural Networks, KNN

7. Data Cleaning and Preprocessing Tool
Develop a tool that automates data cleaning and preprocessing for datasets.
Technologies: Pandas, NumPy, Data Wrangling Techniques

8. Disease Spread Prediction
Use historical data to predict the spread of diseases like COVID-19.
Technologies: Time Series, Regression, Neural Networks

9. Real Estate Price Prediction
Build a model that predicts property prices based on features like location, size, etc.
Technologies: Regression, XGBoost, Random Forests

10. Natural Disaster Prediction (Earthquakes, Floods)
Build a model that can predict natural disasters based on environmental factors and historical data.
Technologies: Time Series, Classification, Regression