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How to Optimize Machine Learning Models for Performance

Optimizing machine learning models for performance is a crucial step in the model development process. A model that is not optimized may pro...

Monday, January 30, 2023

List of ML Algorithms/Terminology

  1. Linear Regression
  2. Logistic Regression
  3. Decision Trees
  4. Random Forest
  5. Neural Networks
  6. Support Vector Machines
  7. k-Nearest Neighbors
  8. k-Means Clustering
  9. Naive Bayes
  10. Gradient Boosting
  11. Principal Component Analysis
  12. Singular Value Decomposition
  13. Lasso Regression
  14. Ridge Regression
  15. Elastic Net
  16. LightGBM
  17. XGBoost
  18. CatBoost
  19. Adaboost
  20. Gradient Descent
  21. Deep Belief Networks
  22. Convolutional Neural Networks
  23. Recurrent Neural Networks
  24. Long Short-Term Memory
  25. Autoencoder
  26. Generative Adversarial Networks
  27. Bagging
  28. Boosting
  29. Random Subspace
  30. Random Patches
  31. Extra Trees
  32. Multi-layer Perceptron
  33. Apriori
  34. Eclat
  35. FP-growth
  36. Page Rank
  37. HMM
  38. CRF
  39. LSTM-CRF
  40. Gaussian Mixture Models
  41. Deep Learning
  42. Stochastic Gradient Descent
  43. Q-Learning
  44. SARSA
  45. DQN
  46. DDQN
  47. A3C
  48. PPO
  49. TRPO
  50. DDPG
  51. TD3
  52. Soft Actor-Critic
  53. Batch Normalization
  54. Dropout
  55. Early Stopping
  56. Adaptive Moment Estimation (Adam)
  57. Root Mean Squared Propagation (RMSProp)
  58. AdaGrad
  59. Natural Gradient Descent
  60. Hessian-Free Optimization
  61. Mini-batch Gradient Descent
  62. Batch Gradient Descent
  63. Stochastic Gradient Descent with Restarts (SGDR)
  64. Adamax
  65. Nadam
  66. Adadelta
  67. RProp
  68. L-BFGS
  69. OWL-QN
  70. Nelder-Mead
  71. Powell
  72. CMA-ES
  73. DE
  74. PSO
  75. Genetic Algorithm
  76. Simulated Annealing
  77. Tabu Search
  78. Scaled Conjugate Gradient
  79. Levenberg-Marquardt
  80. Broyden-Fletcher-Goldfarb-Shanno (BFGS)
  81. Barzilai-Borwein
  82. Trust Region
  83. Conjugate Gradient Descent
  84. Quasi-Newton Method
  85. L-BFGS-B
  86. TNC
  87. COBYLA
  88. SLSQP
  89. trust-exact
  90. trust-krylov
  91. Randomized PCA
  92. Incremental PCA
  93. Kernel PCA
  94. Sparse PCA
  95. Factor Analysis
  96. Independent Component Analysis
  97. Non-negative Matrix Factorization
  98. Latent Dirichlet Allocation
  99. Gaussian Processes
  100. Hidden Markov Models
  101. Conditional Random Fields
  102. Structural SVM
  103. Latent SVM
  104. Multi-task Learning
  105. Transfer Learning
  106. Meta-Learning
  107. One-shot Learning
  108. Few-shot Learning
  109. Zero-shot Learning
  110. Lifelong Learning
  111. Continual Learning
  112. Active Learning
  113. Semi-supervised Learning
  114. Unsupervised Learning
  115. Reinforcement Learning
  116. Adversarial Training
  117. GANs
  118. Variational Autoencoders
  119. Deep Generative Models
  120. Predictive Modeling
  121. Random Forest Classifier
  122. Random Forest Regressor
  123. Extra Trees Classifier
  124. Extra Trees Regressor
  125. AdaBoost Classifier
  126. AdaBoost Regressor
  127. Bagging Classifier
  128. Bagging Regressor
  129. Gradient Boosting Classifier
  130. Gradient Boosting Regressor
  131. XGBoost Classifier
  132. XGBoost Regressor
  133. LightGBM Classifier
  134. LightGBM Regressor
  135. CatBoost Classifier
  136. CatBoost Regressor
  137. Decision Tree Classifier
  138. Decision Tree Regressor
  139. KNN Classifier
  140. KNN Regressor
  141. Logistic Regression Classifier
  142. Logistic Regression Regressor
  143. Naive Bayes Classifier
  144. Naive Bayes Regressor
  145. SVM Classifier
  146. SVM Regressor
  147. MLP Classifier
  148. MLP Regressor
  149. RNN Classifier
  150. RNN Regressor
  151. LSTM Classifier
  152. LSTM Regressor
  153. CNN Classifier
  154. CNN Regressor
  155. Autoencoder Classifier
  156. Autoencoder Regressor
  157. GAN Classifier
  158. GAN Regressor
  159. VAE Classifier
  160. VAE Regressor
  161. Transformer Classifier
  162. Transformer Regressor
  163. BERT Classifier
  164. BERT Regressor
  165. RoBERTa Classifier
  166. RoBERTa Regressor
  167. XLNet Classifier
  168. XLNet Regressor
  169. ALBERT Classifier
  170. ALBERT Regressor
  171. Quadratic Discriminant Analysis
  172. Linear Discriminant Analysis
  173. Multi-Layer Perceptron
  174. Radial Basis Function Network
  175. Self-Organizing Map
  176. Hopfield Network
  177. Boltzmann Machine
  178. Restricted Boltzmann Machine
  179. Deep Belief Network
  180. Convolutional Neural Network
  181. Recurrent Neural Network
  182. Long Short-Term Memory Network
  183. Gated Recurrent Unit
  184. Echo State Network
  185. Attention Mechanism
  186. Transformer
  187. BERT
  188. RoBERTa
  189. XLNet
  190. ALBERT
  191. U-Net
  192. YOLO
  193. Faster R-CNN
  194. Mask R-CNN
  195. RetinaNet
  196. DenseNet
  197. ResNet
  198. Inception
  199. Xception
  200. MobileNet
  201. SqueezeNet
  202. ShuffleNet
  203. EfficientNet
  204. Neural Style Transfer
  205. Generative Adversarial Networks
  206. Variational Autoencoders
  207. Wasserstein GAN
  208. StyleGAN
  209. BigGAN
  210. Flow-based Generative Models
  211. Random Projections
  212. Locally Linear Embedding
  213. Isomap
  214. Multidimensional Scaling
  215. t-Distributed Stochastic Neighbor Embedding
  216. Spectral Clustering
  217. Affinity Propagation
  218. Mean-Shift Clustering
  219. DBSCAN
  220. OPTICS
  221. Birch
  222. K-Means Clustering
  223. Hierarchical Clustering
  224. Expectation Maximization
  225. Gaussian Mixture Model
  226. Hidden Markov Model
  227. Viterbi algorithm
  228. Baum-Welch algorithm
  229. Kalman filter
  230. Particle filter
  231. Sequential Monte Carlo
  232. Markov Chain Monte Carlo
  233. Metropolis-Hastings algorithm
  234. Hamiltonian Monte Carlo
  235. Gibbs sampling
  236. Variational Bayesian Inference
  237. Expectation Propagation
  238. Laplace Approximation
  239. Variational Inference
  240. Markov Chain Monte Carlo Variational Inference
  241. Structured Variational Inference
  242. Black Box Variational Inference
  243. Stochastic Gradient Variational Bayes
  244. Automatic Differentiation Variational Inference
  245. Bayesian Neural Networks
  246. MC Dropout
  247. Bayesian Convolutional Neural Networks
  248. Bayesian Recurrent Neural Networks
  249. Bayesian Attention Networks
  250. Bayesian Transformer Models
  251. Gradient Boosting
  252. XGBoost
  253. LightGBM
  254. CatBoost
  255. Random Forest
  256. Extra Trees
  257. Bagging
  258. AdaBoost
  259. Stochastic Gradient Boosting
  260. Gradient Boosted Regression Trees
  261. Random Survival Forest
  262. Conditional Inference Trees
  263. Random Forest Survival
  264. Random Survival Forest
  265. Random Survival Forest with Interval Censoring
  266. Random Forest with Rotation Forest
  267. Random Forest with Rotation Forest and Interval Censoring
  268. Random Forest with Rotation Forest and Interval Censoring and Survival
  269. Random Survival Forest with Rotation Forest
  270. Random Survival Forest with Rotation Forest and Interval Censoring
  271. Random Survival Forest with Rotation Forest and Interval Censoring and Survival
  272. Random Forest with Rotation Forest and Interval Censoring and Survival with Boosting
  273. Random Survival Forest with Rotation Forest and Interval Censoring and Survival with Boosting
  274. Principal Component Analysis
  275. Independent Component Analysis
  276. Non-Negative Matrix Factorization
  277. Factor Analysis
  278. Canonical Correlation Analysis
  279. Multivariate Adaptive Regression Splines
  280. Locally Estimated Scatterplot Smoothing
  281. Generalized Additive Models
  282. Generalized Linear Models
  283. Generalized Estimating Equations
  284. Generalized Linear Mixed Models
  285. Generalized Additive Mixed Models
  286. Generalized Linear Models with Covariate-Dependent Random Effects
  287. Generalized Estimating Equations with Covariate-Dependent Random Effects
  288. Generalized Linear Mixed Models with Covariate-Dependent Random Effects
  289. Generalized Additive Mixed Models with Covariate-Dependent Random Effects
  290. Generalized Linear Models with Spatial Random Effects
  291. Generalized Estimating Equations with Spatial Random Effects
  292. Generalized Linear Mixed Models with Spatial Random Effects
  293. Generalized Additive Mixed Models with Spatial Random Effects
  294. Generalized Linear Models with Spatio-Temporal Random Effects
  295. Generalized Estimating Equations with Spatio-Temporal Random Effects
  296. Generalized Linear Mixed Models with Spatio-Temporal Random Effects
  297. Generalized Additive Mixed Models with Spatio-Temporal Random Effects
  298. Generalized Linear Models with Spatio-Temporal-Structured Random Effects
  299. Generalized Estimating Equations with Spatio-Temporal-Structured Random Effects
  300. Generalized Linear Mixed Models with Spatio-Temporal-Structured Random Effects
  301. Generalized Additive Mixed Models with Spatio-Temporal-Structured Random Effects
  302. Generalized Linear Models with Spatio-Temporal-Structured-Cross-Sectional Random Effects
  303. Generalized Estimating Equations with Spatio-Temporal-Structured-Cross-Sectional Random Effects
  304. Generalized Linear Mixed Models with Spatio-Temporal-Structured-Cross-Sectional Random Effects
  305. Generalized Additive Mixed Models with Spatio-Temporal-Structured-Cross-Sectional Random Effects
  306. Generalized Linear Models with Spatio-Temporal-Structured-Cross-Sectional-Longitudinal Random Effects
  307. Generalized Estimating Equations with Spatio-Temporal-Structured-Cross-Sectional-Longitudinal Random Effects
  308. Generalized Linear Mixed Models with Spatio-Temporal-Structured-Cross-Sectional-Longitudinal Random Effects
  309. Generalized Additive Mixed Models with Spatio-Temporal-Structured-Cross-Sectional-Longitudinal Random Effects