Week 6 This week’s topic is learning from observation where we learned about a technique used in unsupervised learning which is the clustering technique. Clustering techniques apply when there is no class to be predicted but rather when the instances … Continue reading →

Week 5 This week we learned about the different types of machine learning such as supervised learning, unsupervised learning, and reinforcement learning. We also learned about the naive bayes classifier. Supervised learning, in the context of artificial intelligence (AI) and machine learning, is … Continue reading →

Week 4 This week, we learned about adversarial search and we learned how it is used in games such as chess, tic-tac-toe, backgammon, and etc, to calculate the optimal move. These games are classified by how much information the agent … Continue reading →

Week 3 This week we learned about Informed Search(Best First Search, Greedy Search, & A* Search) and Local Search(Hill Climbing, Simulated Annealing, & Genetic Algorithm). Informed searches uses domain knowledge to guide selection of the best path to continue searching. … Continue reading →