Machine Learning
ได้ดูคลิป บรรยายเรื่อง AI in Cardiac Imaging ศ.นพ. James Min รังสีแพทย์อเมริกัน บรรยายเมื่อปี 2020
https://youtu.be/Y7JDjSYlER4&t=800
มีสไลด์แผนภูมิ Machine Learning Algorithm น่าสนใจ สำหรับผู้ต้องการศึกษาเรื่อง Artificial Intelligence จึงนำไปค้นหาเพิ่มเติม
1 Deep Learning
1.1 Deep Boltzmann Machine (DBM)
1.2 Deep Belief Networks (DBN)
1.3 Convolutional Neural Networks (CNN)
1.4 Stacked Auto Encoders
2 Ensemble
2.1 Random Forest
2.2 Gradient Boosting Machines (GBM)
2.3 Boosting
2.4 Bootstrapped Aggregation (Bagging)
2.5 AdaBoost
2.6 Stacked Generalization (Blending)
2.7 Gradient Boosted Regression Trees (GBRT)
3 Neural Networks
3.1 Radial Basis Function Network (RBFN)
3.2 Perceptron
3.3 Back-Propagation
3.4 Hopfield Network
4 Regularization
4.1 Ridge Regression
4.2 Least Absolute Shrinkage and Selector Operator (LASSO)
4.3 Elastic Net
4.4 Least Angle Regression (LARS)
5 Rule System
5.1 Cubist
5.2 One Rule (OneR)
5.3 Zero Rule (ZeroR)
5.4 Repeated Incremental Pruning to Produce Error Reduction (RIPPER)
6 Regression
6.1 Linear Regression
6.2 Ordinary Least Squares Regression (OLSR)
6.3 Stepwise Regression
6.4 Multivariate Adaptive Regression Splines (MARS)
6.5 Locally estimated Scatterplot Smoothing (LOESS)
6.6 Logistic Regression
7 Bayesian
7.1 Naive Bayes
7.2 Averages One-Dependence Estimators (AODE)
7.3 Bayesian Belief Network (BBN)
7.4 Gaussian Naive Bayes
7.5 Multinomial Naive Bayes
7.6 Bayesian Network (BN)
8 Decision Tree
8.1 Classification and Regression Tree (CART)
8.2 Iterative Dichotomiser 3 (ID3)
8.3 C4.5
8.4 C5.0
8.5 Chi-squared Automatic Interaction Detection (CHAID)
8.6 Decision Stump
8.7 Conditional Decision Trees
8.8 M5
9 Dimensionality Reduction
9.1 Principal Component Analysis (PCA)
9.2 Partial Least Squares Regression (PLSR)
9.3 Sammon Mapping
9.4 Multidimensional Scaling (MDS)
9.5 Projection Pursuit
9.6 Principal Component Regression (PCR)
9.7 Partial Least Squares Discriminant Analysis
9.8 Mixture Discriminant Analysis
9.9 Quadratic Discriminant Analysis (QDA)
9.10 Regularized Discriminant Analysis (RDA)
9.11 Flexible Discriminant Analysis (FDA)
9.12 Linear Discriminant Analysis (LDA)
10 Instance Based
10.1 k-Nearest Neighbor (kNN)
10.2 Learning Vector Quantization (LVQ)
10.3 Sell-Organizing Map (SOM)
10.4 Locally Weighted Learning (LWL)
11 Clustering
11.1 k-Means
11.2 k-Medians
11.3 Expectation Maximization
11.4 Hierarchical Clustering
ลิงค์ที่เกี่ยวข้อง
** Data Science วิชาใหม่ที่น่าสนใจแห่งศตวรรษที่ 21
https://www.gotoknow.org/posts/711665
ความเห็น (1)
A good starting point ‘bibliography’! Thank you.