Index

• A
• B
• C
• D
• F
• G
• H
• K
• L
• M
• N
• O
• P
• Q
• R
• S
• T
• U

A

• activation function
• Affine function
• \(\alpha\)-sublevel set
• arg min

B

• Backpropagation
• Bag of Words
• Bias trick
• Binary classifiers
  • one-vs-one
  • Hierarchical
  • Binary coding
  • one-vs-rest or one-hot coding (2)

C

• CIFAR-10
• Classification
• Clustering
  • K-means Clustering
• Collaborative Filtering
  • Item-item Collaborative Filtering
  • Matrix Factorization Collaborative Filtering
  • Neighborhood-based
  • User-user Collaborative Filtering
• Convex combination
• Convex function
  • First-order condition
  • Second-order condition
• Convex hull
• Convex optimization problems
• Covariance Matrix
• Convex sets
• Cross entropy
• Cross validation

D

• Dimensionality Reduction 2

F

• Feature Engineering
  • Feature selection
  • Dimensionality reduction
  • Feature Scaling and Normalization

G

• Geometric Programming
• Gradient Descent (GD)
  • Batch Gradient Descent
  • Mini-batch Gradient Descnet
  • Momentum
  • Nesterov accelerated gradient (NAG)
  • Stochastic Gradient Descent (SGD)
• Ground truth

H

• Hidden layer
• Hinge loss

K

• K-means Clustering
• K-nearest neighbors
• Kernel functions

L

• Large-sclae problem
• Level sets
• Linear Programming
• Linearly separable
• Locally optimal points
• Logistic Regression
• Loss function (Hàm mất mát) (2)
• Low-rank approximation

M

• Matrix Factorization
• MovieLens 100k
• Multi-layer Perceptron

N

• Neural Networks
• Newton’s Method
• Norms (chuẩn)
• Norm balls

O

• Objective function
• Online Learning
• Orthogonal basis and matrices

P

• Perceptron Learning Algorithm
• Pocket Algorithm
• Positive Semidefinite Matrices
• Principal Component Analysis

Q

• Quadratic form
• Quadratic programming

R

• Recommendation Systems
• Regression
  • Linear Regression
• Reinforement Learning (Học Củng Cố)
• Rectified Linear Unit (ReLU)
• Regularization

S

• Semi-supervised Learning (Học Bán Giám Sát)
• Sigmoid function
• Similarity function
• Singular Value Decomposition - SVD
  • Compact SVD
  • Truncated SVD
• Softmax Regression
  • Softmax function
• Supervised Learning (Học Có Giám Sát)
• Support vector machine
  • Hard Margin
  • Hinge loss
  • Kernel SVM
  • Multi-class SVM
  • Soft Margin

T

• Training data (dữ liệu huấn luyện)

U

• Utility Matrix
• Unsupervised Learning (Học Không Giám Sát)