Adil Hussain
Linear Regression Logistic Regression Decision Trees Random Forest Support Vector Machines (SVM) Naive Bayes K-Nearest Neighbors (KNN) K-Means Clustering Hierarchical Clustering Principal Component Analysis (PCA) Gradient Boosting Machines (GBM) AdaBoost Neural Networks (Deep Learning) Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN) Long Short-Term Memory Networks (LSTM) Gated Recurrent Units (GRU) Autoencoders Generative Adversarial Networks (GANs) Reinforcement Learning (Q-Learning, Deep Q-Learning, etc.)
There are several machine learning algorithm techniques considering the types such as supervised, unsupervised, semi-supervised, and Reinforcement learning. here is the list of techniques:
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Andrius Ambrutis
Mr. Adil Hussain already named a lot of them, but I will add that Artificial Neural Networks alone has maybe 30 different variations with new type being introduced yearly or even monthly, and we cannot list them all. I will add links with some nice ANN variations:
https://towardsai.net/p/machine-learning/main-types-of-neural-networks-and-its-applications-tutorial-734480d7ec8e
https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464
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