Objective: Build a simple chatbot that responds to user inputs based on predefined rules.
- Use
if-else
statements or pattern matching techniques to identify user queries and provide appropriate responses. - Gain a basic understanding of natural language processing and conversation flow.
Objective: Create an AI agent that plays the classic game of Tic-Tac-Toe against a human player.
- Implement algorithms like Minimax (with or without Alpha-Beta Pruning) to make the AI unbeatable.
- Learn about game theory and basic search algorithms.
Objective: Combine computer vision and natural language processing to build an image captioning AI.
- Use pre-trained image recognition models like VGG or ResNet to extract image features.
- Utilize a recurrent neural network (RNN) or transformer-based model to generate captions.
Objective: Develop a recommendation system that suggests items to users based on their preferences.
- Use techniques like collaborative filtering or content-based filtering.
- Suggest movies, books, or products to users.
Objective: Build an AI application that can detect and recognize faces in images or videos.
- Use pre-trained face detection models like Haar cascades or deep learning-based face detectors.
- Optionally, add face recognition capabilities using techniques like Siamese networks or ArcFace.