Intelligent Systems Projects

Contents of each project

CA1

• Gradient descent
• Stochastic gradient descent
• Simulated annealing
• Support Vector Machines (SVM) classification

CA2

• Decision trees
• Random forests
• KNN
  • NCA
  • LMNN

CA3

• Neural networks for classification of CIFAR10
• Dropout
• Padding
• Stride
• Max-pooling
• ReLU
• Tanh
• Backpropagation

CA4

• K-means clustering
• hierarchical clustering
• Logestic regression
• Central Limit Theroem
• Birthday problem

CA5

• Naive Bayes classifier
• Dynamic programming
• Policy iteration
• Value iteration
• Q-learning