Machine Learning Algorithms

1. Supervised Learning

a. Regression

• Linear Regression
• Polynomial Regression
• Ridge/Lasso Regression

b. Classification

• K-Nearest Neighbour (K-NN)
• Naive Bayes
• Logistic Regression
• Support Vector Machine (SVM)
• Decision Trees

2. Unsupervised Learning

a. Clustering

• K-means
• Aggolomerative clustering
• DBSCAN
• Mean Shift
• Fuzzy C-means

b. Association Rule Learning

• FP Growth
• Apriori

c. Dimensionality Reduction

• Principal Component Analysis (PCA)
• Singular Value Decomposition (SVD)

3. Neural Networks and Deep Learning

a. CNN (Convolutional Neural Networks)

• DCNN

b. RNN (Recurrent Neural Networks)

• LSM
• LSTM
• GRU

c. GAN (Generative Adversarial Networks)

d. Autoencoders

• seq2seq

e. Perceptrons