Regression models

Discriminative model

Discriminative models, also referred to as conditional models, are a class of logistical models used for classification or regression. They distinguish decision boundaries through observed data, such as pass/fail, win/lose, alive/dead or healthy/sick. Typical discriminative models include logistic regression (LR), conditional random fields (CRFs) (specified over an undirected graph), decision trees, and many others. Typical generative model approaches include naive Bayes classifiers, Gaussian mixture models, variational autoencoders, generative adversarial networks and others. (Wikipedia).

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generative model vs discriminative model

understanding difference between generative model and discriminative model with simple example. all machine learning youtube videos from me, https://www.youtube.com/playlist?list=PLVNY1HnUlO26x597OgAN8TCgGTiE-38D6

From playlist Machine Learning

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How to use the discriminat to describe your solutions

πŸ‘‰ Learn how to determine the discriminant of quadratic equations. A quadratic equation is an equation whose highest power on its variable(s) is 2. The discriminant of a quadratic equation is a formula which is used to determine the type of roots (solutions) the quadratic equation have. T

From playlist Discriminant of a Quadratic Equation

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Algebra - Ch. 27: The Discriminant (1 of 11) What is the Discriminant?

Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn what is the discriminant of a quadratic equation and how the determinant determines the if the quadratic equation has 2

From playlist ALGEBRA CH 27 THE DISCRIMINANT

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(ML 1.5) Generative vs discriminative models

A broad overview. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA

From playlist Machine Learning

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What is the discriminant and what does it mean

πŸ‘‰ Learn all about the discriminant of quadratic equations. A quadratic equation is an equation whose highest power on its variable(s) is 2. The discriminant of a quadratic equation is a formula which is used to determine the type of roots (solutions) the quadratic equation have. The disc

From playlist Discriminant of a Quadratic Equation | Learn About

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Determine and describe the discriminant

πŸ‘‰ Learn how to determine the discriminant of quadratic equations. A quadratic equation is an equation whose highest power on its variable(s) is 2. The discriminant of a quadratic equation is a formula which is used to determine the type of roots (solutions) the quadratic equation have. T

From playlist Discriminant of a Quadratic Equation

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What is the formula for a perfect square trinomial and how does the discriminant fit in

πŸ‘‰ Learn all about the discriminant of quadratic equations. A quadratic equation is an equation whose highest power on its variable(s) is 2. The discriminant of a quadratic equation is a formula which is used to determine the type of roots (solutions) the quadratic equation have. The disc

From playlist Discriminant of a Quadratic Equation | Learn About

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247 - Conditional GANs and their applications

Conditional Generative Adversarial Network cGAN A GAN model generates a random image from the domain. The relationship between points in the latent space and the generated images is hard to map. A GAN can be trained so that both the generator and the discriminator models are conditioned

From playlist Generative Adversarial Networks

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DeepMind x UCL | Deep Learning Lectures | 9/12 | Generative Adversarial Networks

Generative adversarial networks (GANs), first proposed by Ian Goodfellow et al. in 2014, have emerged as one of the most promising approaches to generative modeling, particularly for image synthesis. In their most basic form, they consist of two "competing" networks: a generator which trie

From playlist Learning resources

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[Classic] Generative Adversarial Networks (Paper Explained)

#ai #deeplearning #gan GANs are of the main models in modern deep learning. This is the paper that started it all! While the task of image classification was making progress, the task of image generation was still cumbersome and prone to artifacts. The main idea behind GANs is to pit two

From playlist Papers Explained

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Padma Srinivasan - Conductors and minimal discriminants of hyperelliptic curves - AGONIZE conference

Conductors and minimal discriminants are two measures of degeneracy of the singular fiber in a family of hyperelliptic curves. In genus one, the Ogg–Saito formula shows that these two invariants are equal, and in genus two, Qing Liu showed that they are related by an inequality. In this ta

From playlist Arithmetic Geometry is ONline In Zoom, Everyone (AGONIZE)

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CMU Neural Nets for NLP 2017 (17): Adversarial Learning

This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers: * (Generative) Adversarial Networks * Where to use the Adversary?: Features vs. Outputs * GANs on Discrete Outputs * Adversaries on Features Slides: http://phontron.com/class/nn4nlp2017/assets/

From playlist CMU Neural Nets for NLP 2017

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Elliptic Curves - Lecture 17b - Elliptic curves over local fields (minimal discriminant)

This video is part of a graduate course on elliptic curves that I taught at UConn in Spring 2021. The course is an introduction to the theory of elliptic curves. More information about the course can be found at the course website: https://alozano.clas.uconn.edu/math5020-elliptic-curves/

From playlist An Introduction to the Arithmetic of Elliptic Curves

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What Are GANs? | Generative Adversarial Networks Explained | Deep Learning With Python | Edureka

πŸ”₯ Post Graduate Diploma in Artificial Intelligence by E&ICT Academy NIT Warangal: https://www.edureka.co/executive-programs/machine-learning-and-ai This Edureka video on 'What Are GANs' will help you understand the concept of generative adversarial networks including how it works and the t

From playlist Deep Learning With TensorFlow Videos

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Gentle Intro to Generative Adversarial Networks - Part 1 (GANs)

Join my Foundations of GNNs online course (https://www.graphneuralnets.com)! This video gives a high-level overview of Generative Adversarial Networks (GANs). A simple coin-flip example demonstrates the key aspects of adversarial learning. 3-part blog series: Part 1: https://blog.zakj

From playlist Generative Adversarial Networks

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Introduction to GANs, NIPS 2016 | Ian Goodfellow, OpenAI

NIPS 2016 Workshop on Adversarial Training http://www.iangoodfellow.com/slides/2016-12-9-gans.pdf https://arxiv.org/abs/1701.00160 Introduction to Generative Adversarial Networks

From playlist Introduction to Deep Learning

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Overview of solutions of a quadratic function and the discriminant

πŸ‘‰ Learn all about the discriminant of quadratic equations. A quadratic equation is an equation whose highest power on its variable(s) is 2. The discriminant of a quadratic equation is a formula which is used to determine the type of roots (solutions) the quadratic equation have. The disc

From playlist Discriminant of a Quadratic Equation | Learn About

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Paper Read Aloud: Evaluation Examples Are Not Equally Informative: Should NLP Leaderboards Change?

An experiment! I recorded this a while ago but didn't post it until now because ... 2020. A long time ago, a blind student once asked me to record myself reading my papers when he found that I do that anyway during my editing process, so I finally did it. This is an experiment, feedback

From playlist Papers Read Aloud

Related pages

Logistic regression | Bayes' theorem | Naive Bayes classifier | Regression analysis | Linear classifier | Generative adversarial network | Generative model | Principal component analysis | Statistical classification | Generalized linear model | Posterior probability | Linear discriminant analysis | Linear regression | Joint probability distribution | Autoencoder | Conditional random field | Categorical distribution | Bernoulli distribution | Conditional probability distribution