CS540_Intro_to_Artificial_Intelligence

Learn basic concept of Artificial Intelligence

1. Mathematical concept
2. Supervised/unsupervised learning, reinforcement learning
3. Neural networks and search trees
4. Game theory

💻 HW2: Probabilisitic Language Identification

1. Simple practice for coding with python (counting letter)
2. Programming practice with Bayes' rule

💻 HW3: Prinicipal Component Analysis (PCA)

1. Using Numpy for image projection with Eigenvalues and Eigenvectors
2. Familiarize myself with the python packages (Numpy, Scipy, matplotlib)

💻 HW4: Clustering

1. Process the real-world data to perform complete linkage hierarchical agglomerate clustering
2. Visualize the clustering process

💻 HW5: Linear Regression

1. Application of Linear regression on a period of Lake-mendota Ice (real world dataset)
2. Visualize the curated data

💻 HW6: Neural Network

Using pytorch and Fashion-MNIST for neural network (build model -> train model -> evaluate model -> predict labels)

💻 HW7: Convolutional Neural Network (CNN)

1. Apply ML to image classification
2. Experience LeNet architecture
3. Construct Convolutional Neural Networks (CNNs) with MiniPlaces Dataset and training

💻 HW8: A* algorithm on the 7-tile puzzle

1. Implement A* algorithm on 7-tile puzzle by using heuristic function and priority queue
2. Deepen understanding of state space generation.

💻 HW10: Reinforcement Learning

Implement Q-learning of Reinforcement Learning with OpenAI gym Environment