Taxonomy of the most commonly used Machine Learning Algorithms

By Murat Durmus

"All models are wrong, but some are useful." George E. P. Box

Taxonomy of 40 Machine Learning Algorithms:

- ADABOOST
- ADAM OPTIMIZATION
- AGGLOMERATIVE CLUSTERING
- ARMA/ARIMA MODEL
- BERT
- CONVOLUTIONAL NEURAL NETWORK
- DBSCAN
- DECISION TREE
- DEEP Q-LEARNING
- EFFICIENTNET
- FACTOR ANALYSIS OF CORRESPONDENCES
- GAN
- GMM
- GPT-3
- GRADIENT BOOSTING MACHINE
- GRADIENT DESCENT
- GRAPH NEURAL NETWORKS
- HIERARCHICAL CLUSTERING
- HIDDEN MARKOV MODEL (HMM)
- INDEPENDENT COMPONENT ANALYSIS
- ISOLATION FOREST
- K-MEANS
- K-NEAREST NEIGHBOUR
- LINEAR REGRESSION
- LOGISTIC REGRESSION
- LSTM
- MEAN SHIFT
- MOBILENET
- MONTE CARLO ALGORITHM
- MULTIMODAL PARALLEL NETWORK
- NAIVE BAYES CLASSIFIERS
- PROXIMAL POLICY OPTIMIZATION
- PRINCIPAL COMPONENT ANALYSIS
- Q-LEARNING
- RANDOM FORESTS
- RECURRENT NEURAL NETWORK
- RESNET
- SPATIAL TEMPORAL GRAPH CONVOLUTIONAL NETWORKS
- STOCHASTIC GRADIENT DESCENT
- SUPPORT VECTOR MACHINE

• Format: Paperback
• Language: English
• ISBN: B09WQB2N2B
• ISBN13: 9798442041989
• Release Date: March 2022
• Publisher: Independently Published
• Length: 84 Pages
• Weight: 0.20 lbs.
• Dimensions: 0.2" x 5.0" x 8.0"