AI Assignments
Hands-on assignments to master artificial intelligence. From foundational concepts to advanced projects, build real-world AI applications and develop practical skills through guided exercises.
Linear Regression Model
Build your first ML model from scratch. Implement linear regression to predict house prices using gradient descent and evaluate model performance with metrics.
CNN Image Classifier
Design and train a Convolutional Neural Network using TensorFlow or PyTorch. Classify images from CIFAR-10 dataset and implement data augmentation techniques.
Sentiment Analysis System
Build an NLP model to analyze sentiment in product reviews. Use transformers or LSTM networks to classify text as positive, negative, or neutral sentiment.
Movie Recommender System
Create a collaborative filtering system for movie recommendations. Implement both user-based and item-based filtering using the MovieLens dataset.
Real-time Object Detection
Implement YOLO or Faster R-CNN for real-time object detection. Process video streams and identify multiple objects with bounding boxes and confidence scores.
Conversational AI Chatbot
Build an intelligent chatbot using transformer models. Implement context awareness, intent recognition, and generate human-like responses using GPT or BERT.
Stock Price Forecasting
Predict stock prices using LSTM or GRU networks. Handle time series data, implement feature engineering, and evaluate forecasting accuracy with RMSE.
Generate Images with GANs
Create synthetic images using Generative Adversarial Networks. Train generator and discriminator networks to produce realistic faces or artwork.
Customer Segmentation
Segment customers using K-Means clustering. Analyze customer behavior patterns, visualize clusters, and derive actionable business insights from data.
Train Gaming AI Agent
Use Q-Learning or Deep Q-Networks to train an agent to play games. Implement reward systems, explore-exploit strategies, and optimize agent performance.
AI Ethics & Bias Analysis
Research ethical implications of AI systems. Analyze bias in AI models, explore fairness metrics, and propose solutions for responsible AI development.
Build Neural Network from Scratch
Implement a feedforward neural network without using libraries. Code forward propagation, backpropagation, and gradient descent from first principles.