K-nearest neighbor
When we refer Supervised Learning,the first question comes that algorithmic program ought to be used that is easy to know […]
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December 2020
MACHINE LEARNING
Introduction to machine learning Source : https://www.ie.edu/exponential-learning/blog/data-science/machine-learning-marketing/ 1. “Data is the new oil” If we consider 10-15 years back we
Computational Learning Theory And PAC
Many times while making any decision, you come across some factors which prompt you to take the decision while some
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Clustering and its applications
Getting familiar with Clustering Many items about us can be classified as this and that,” or we have groupings that
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Ensemble Learning
SOURCE:https://miro.medium.com/max/1075/1*10t9S7xvWE5Z3NEZrmHG2w.jpeg When teaching machine learning algorithms, the bias-variance trade-off is a problem we both face. Bagging is a powerful tool
Bayesian Learning And Gibbs Sampling
The likeliness of an event to occur or the proposition to be true is known as the probability of an
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Hypothesis Space And Inductive Bias
Why and how to predict Hypothesis Space And Inductive Bias? Predictions have become very essential in our lives today. From
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ARTIFICIAL INTELLIGENCE VS MACHINE LEARNING
AI is a huge hype nowadays and people benefit from it every day from Netflix to music recommender systems, Google
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