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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