Artificial Intelligence and Machine Learning

khokon12

• Neural networks: Use graphs to represent the interconnected neurons and weights.
• Decision trees: Employ trees to make decisions based on features and their values.
• Pattern recognition: Use data structures like hash tables or feature vectors to represent and compare patterns.
  

• Collision detection: Use data structures like quadtrees or spatial hashing to efficiently detect collisions between objects.
• Pathfinding: Employ graphs and Phone Number algorithms like A* search to find optimal paths for characters.
• Level design: Use data structures to represent and manipulate game levels and objects.
  

• Numerical simulations: Use arrays and matrices to represent and manipulate numerical data.
• Data analysis: Employ data structures like histograms, scatter plots, or line graphs to visualize and analyze data.
• Scientific visualization: Use data structures to represent and display scientific data in visual form.