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bayesian network

Bayesian Networks : An Introduction | What is Bayesian Networks and Definition?

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Contributed by: Rachit Jain LinkedIn profile: https://www.linkedin.com/in/rachit-jain-37b63677/ The Bayesian network has given shape to most of the complex problems that provide less information and resources. It has been implemented in most of the advanced technologies like Artificial Intelligence and Machine learning. What is a Bayesian Network? A Bayesian network falls under the category of Probabilistic […]

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model evaluation metrics

Famous Machine Learning Metrics | Model Evaluation Metrics for Machine Learning

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Introduction Model and Performance Matrix Match Type of cut off approach in classification model Regression model performance parameters Classification model performance parameters Model Stability Contributed by: Rishabh Pandey LinkedIn profile: https://www.linkedin.com/in/rishabh1409/ Introduction Whenever you build a statistical or Machine Learning model, all the audiences including business stakeholders have only one question, what is model performance?

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machine learning resume

Machine Learning Resume : Sample and Writing guide

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Creating your Machine Learning Resume In a data-driven era where insights hold the key to unlocking innovation, machine learning has emerged as a game-changer. Imagine a world where algorithms learn from data, uncover patterns, and make intelligent predictions. As you venture into the realm of machine learning, your resume becomes the gateway to landing your

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Maximum likelihood estimation

Maximum Likelihood Estimation: What Does it Mean?

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Contributed by: Venkat Murali LinkedIn Profile: https://www.linkedin.com/in/venkat-murali-3753bab/ The maximum likelihood estimation is a method that determines values for parameters of the model. It is the statistical method of estimating the parameters of the probability distribution by maximizing the likelihood function. The point in which the parameter value that maximizes the likelihood function is called the maximum

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goodness of fit test

Understanding Goodness of Fit Test, Definition | What is Goodness of Fit?

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Contributed by: Rahul SinghLinkedIn Profile: https://www.linkedin.com/in/rahul-singh-3b213117/ What is the goodness of fit? A goodness-of-fit is a statistical technique. It is applied to measure “how well the actual(observed) data points fit into a Machine Learning model”. It summarizes the divergence between actual observed data points and expected data points in context to a statistical or Machine

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An Introduction to Hill Climbing Algorithm in AI (Artificial Intelligence)

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Hill Climbing Algorithm Working Process Types of Hill Climbing State Space Concept for Hill Climbing Problems faced in Hill Climbing Algorithm Case Study Introduction There are diverse topics in the field of Artificial Intelligence and Machine learning. Research is required to find optimal solutions in this field. In Deep learning, various neural networks are used

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GAN

Introduction to Generative Adversarial Networks (GANs)

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Supervised vs Unsupervised learning What are Generative Models? What are GANs? Where are GANs used? Tips for training GANs Generating MNIST Handwritten Digit  Supervised vs Unsupervised Learning In Supervised Learning, we train the machine using data that is well “labeled”. It means the data is already tagged with the correct answer. A supervised learning algorithm

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