Machine Learning
Explore the core techniques of Machine Learning – the engine behind modern data science.
Dive into Supervised, Unsupervised, and Reinforcement Learning, each with practical algorithms and real-world applications.
Click on any method to understand how it works, where it's used, and how it can power smarter decisions.
Logistic RegressionDecision TreesSupport Vector Machines(SVM)Naïve BayesK-Nearest NeighborsGradient Boosting Random ForestsModel Evaluation MetricsK-Means Clustering Hierarchical Clustering DBSCANMean Shift Gaussian Mixture Models(GMM)Principal Component AnalysisT-SNE (t-distributed stochastic neighbor embedding)Autoencoders(Neural Network based) Q-learningDeep Q-Networks (DQN)SARSAPolicy Gradient ModelsProximal Policy Optimization Deep Deterministic Policy Gradient (DDPG)A3C (Asynchronous Advantage Actor – Critic)
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