Regular semantics

Regular Expressions

From playlist Computing for Data Analysis (Roger Peng)

1.7 Regular Expressions

From playlist Information Service Engineering by Dr. Harald Sack and Dr. Maria Koutraki

Computational Semantics: How Computers Know what Words Mean [Lecture]

This is a single lecture from a course. If you you like the material and want more context (e.g., the lectures that came before), check out the whole course: https://boydgraber.org/teaching/CMSC_723/ (Including homeworks and reading.) Music: https://soundcloud.com/alvin-grissom-ii/review

From playlist Computational Linguistics I

Summary Simplifying rational expressions

Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational

From playlist Simplify Rational Expressions

Simplify a rational expression

Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational

From playlist Simplify Rational Expressions

REGEX Tutorial Regular Expressions

Best Regular Expressions Book : http://goo.gl/RFX7eJ Here I explain how Regular Expressions are used. I cover all of the codes and what they are used for. The goal is to teach you how to use regular expressions once and for all.

From playlist Regex Tutorial

Regular Expressions Introduction

This video provides a brief overview of regular expressions and basic Go examples.

From playlist Archive - Cloud Computing

PSY 523 Reading Part 2

Lecturer: Dr. Erin M. Buchanan Missouri State University Summer/Fall 2016 PSY 523 Psychology and Language lectures covering material from Harley's The Psychology of Language: From Data to Theory. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdo

From playlist PSY 523 Psychology and Language

An Overview of Relations and Functions for Linguists - Semantics in Linguistics

In this video on #semantics in #linguistics we introduce relations and functions, talk about properties of relations and types of functions. Join this channel to get access to perks: https://www.youtube.com/channel/UCGYSfZbPp3BiAFs531PBY7g/join Instagram: http://instagram.com/TrevTutorOf

From playlist Semantics in Linguistics

Simplifying rational expression

Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational

From playlist Simplify Rational Expressions (Binomials) #Rational

RubyConf 2021 - Just-in-Time Compiling Ruby Regexps on TruffleRuby by Benoit Daloze and Josef Haider

TruffleRuby together with Truffle Regex can now execute Ruby Regexps up to 40 times faster than CRuby! This is possible by just-in-time compiling Ruby Regexps to machine code by using Truffle Regex, a Truffle language for regular expressions. Truffle Regex uses finite-state machines, a muc

From playlist RubyConf 2021

ACAI: Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer

Toronto Deep Learning Series, 7-Feb-2019 For slides and more information, visit https://tdls.a-i.science/events/2019-02-07 UNDERSTANDING AND IMPROVING INTERPOLATION IN AUTOENCODERS VIA AN ADVERSARIAL REGULARIZER Autoencoders provide a powerful framework for learning compressed representa

From playlist Generative Models

Theory of Computation Recitation 3

Theory of Computation Recitation 3 aduni

From playlist [Shai Simonson]Theory of Computation

Autoencoders - EXPLAINED

Data around us, like images and documents, are very high dimensional. Autoencoders can learn a simpler representation of it. This representation can be used in many ways: - fast data transfers across a network - Self driving cars (Semantic Segmentation) - Neural Inpainting: Completing sect

From playlist Algorithms and Concepts

27c3: Code deobfuscation by optimization (en)

Speaker: Branko Spasojevic Optimization algorithms present an effective way for removing most obfuscations that are used today. Much of the compiler theory can be applied in removing obfuscations and building fast and reliable deobfuscation systems. By understanding traditional optimizati

From playlist 27C3: We come in peace

Lecture 15/16 : Modeling hierarchical structure with neural nets

Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 15A From Principal Components Analysis to Autoencoders 15B Deep Autoencoders 15C Deep autoencoders for document retrieval and visualization 15D Semantic hashing 15E Learning binary codes for image retrieval 15F Shallo

From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]

5.8 Web Ontology Language OWL 5

From playlist Semantic Web Technologies by Dr. Harald Sack

CMU Neural Nets for NLP 2017 (14): Neural Semantic Parsing

This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers: * What is Graph-based Parsing? * Minimum Spanning Tree Parsing * Structured Training and Other Improvements * Dynamic Programming Methods for Phrase Structure Parsing * Reranking Slides: http:/

From playlist CMU Neural Nets for NLP 2017

Simplifying a rational expression by factoring

Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational

From playlist Simplify Rational Expressions

VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained

❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany In this video I cover VQ-GAN or Taming Transformers for High-Resolution Image Synthesis. It uses modified VQ-VAEs and a powerful transformer (GPT-2) to synthesize high-res images. An important modification of V

From playlist Transformers