Certainly, here's a tabular representation of some common machine learning algorithms and their types:
Type | Algorithm |
---|---|
Supervised Learning | |
Linear Regression | |
Logistic Regression | |
Support Vector Machines (SVM) | |
Decision Trees and Random Forests | |
Unsupervised Learning | |
K-Means Clustering | |
Hierarchical Clustering | |
Principal Component Analysis (PCA) | |
Reinforcement Learning | |
Q-Learning | |
Deep Q Network (DQN) | |
Neural Networks | |
Feedforward Neural Networks | |
Convolutional Neural Networks (CNN) | |
Recurrent Neural Networks (RNN) | |
Ensemble Learning | |
Gradient Boosting Machines (GBM) | |
AdaBoost | |
NLP Algorithms | |
Word Embeddings (Word2Vec, GloVe) | |
Recurrent Neural Networks (RNN) | |
Dimensionality Reduction | |
t-Distributed Stochastic Neighbor Embedding (t-SNE) | |
Autoencoders |