The Bayesian approach in ML assigns a probability distribution to all elements, including model parameters and variables. It is often used in probabilistic models and provides a foundation for multiple ML algorithms and techniques, including the following: Naïve Bayes classifier.This common ML algorit...
What are Markov decision processes (MDPs)? What are Markov decision processes (MDPs) and how do they apply to hidden Markov models? What is the Turing Test? What is the k-means algorithm? What is the Apriori algorithm? What are the five popular algorithms of machine learning?Related...
The k-nearest neighbor (KNN) algorithm is another widely used classification method. Although it can be applied to both regression and classification tasks, it is most commonly used for classification. The algorithm assigns a class to a new data point based on the classes of its k nearest neig...
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it becomes all the more critical to ensure that your search algorithm works effectively to fetch and display the most relevant items on the top to get users hooked from the moment they hit the search button. To test how successful your search algorithm is in doing so, you can simply test ...
Model: Also known as “hypothesis”, a machine learning model is the mathematical representation of a real-world process. A machine learning algorithm along with the training data builds a machine learning model. Feature: A feature is a measurable property or parameter of the data-set. ...
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By gradually reducing the error with each iteration, the algorithm eventually converges to a local optimum. Gradient descent is widely used in optimization problems, though the precise mathematical formulation is beyond the scope of this article Alternating least squares: In this approach, we ...
12. Bayesian deep learning Comparison of BNN model and traditional neural network model structure Source:MDPI Non-technical explanation:Imagine a computer learning from uncertainty and incorporating prior knowledge into its decisions. Bayesian deep learning combines the power of deep learning with Bayesian...
This is post will share with you the Naive Bayes. What is Naive Bayes? Naive Bayes algorithm: a simple multi-class classification algorithm based on the Bayes theorem. It assumes that features are independent of each other. For a given sample feature X, the probability that a sample belongs...