🔊NPTEL Introduction to Machine Learning – IITKGP 7 days 5 Quiz Assignment Remedies | July 2022
This system provides a concise introduction to the essential principles in machine learning and preferred machine learning algorithms. We will go over the standard and most popular supervised learning algorithms such as linear regression, logistic regression, conclusion trees, k-closest neighbour, an introduction to Bayesian discovering and the naïve Bayes algorithm, support vector equipment and kernels and neural networks with an introduction to Deep Studying. We will also go over the primary clustering algorithms. Function reduction techniques will also be talked over. We will introduce the basics of computational finding out principle. In the program we will talk about different troubles related to the software of machine learning algorithms. We will examine speculation house, overfitting, bias and variance, tradeoffs in between representational electrical power and learnability, analysis tactics and cross-validation. The training course will be accompanied by arms-on dilemma resolving with programming in Python and some tutorial classes.
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~~Training course Layout~~
7 days 1: Introduction: Essential definitions, forms of understanding, speculation house and inductive bias, analysis, cross-validation
7 days 2: Linear regression, Decision trees, overfitting
7 days 3: Instance dependent studying, Element reduction, Collaborative filtering dependent advice
7 days 4: Probability and Bayes understanding
Week 5: Logistic Regression, Assist Vector Device, Kernel operate and Kernel SVM
7 days 6: Neural network: Perceptron, multilayer community, backpropagation, introduction to deep neural community
Week 7: Computational understanding concept, PAC mastering product, Sample complexity, VC Dimension, Ensemble learning
Week 8: Clustering: k-signifies, adaptive hierarchical clustering, Gaussian combination design
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🔴Textbooks and References:
1. Machine Learning. Tom Mitchell. Very first Version, McGraw- Hill, 1997.
2. Introduction to Machine Learning Version 2, by Ethem Alpaydinal)
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