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 |