Machine Learning
Machine Learning
Unit 1
Supervised Learning Algorithms in ML (Machine Learning)
Decision Trees Tree Pruning Rule-based Classification Support Vector Machines (SVM) k-Nearest Neighbors (k-NN) Random Forest Algorithm
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Why Machine learning (ML), Types of ML problems ,Applications
Machine Learning (ML) encompasses various types, including Supervised, Unsupervised, Semi-Supervised, and Reinforcement Learning
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Regression and Classification in ML (Machine Learning)
Regression predicts numerical values, classification assigns data to predefined categories, confusion matrices evaluate model performance, logistic regression
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Unit 2
Unit 3
Artificial Neural Networks in Machine Learning
The term "Artificial Neural Network" comes from replicating the structure of the human brain, which is composed of biological neural networks.
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Backpropagation and Overfitting in Machine Learning
Backpropagation is a supervised learning algorithm used or employed to train artificial neural networks. It involves the iterative adjustment of network weights.
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