Machine Translation - Lecture 4: IBM Model 1 and the EM Algorithm

preview_player
Показать описание
IBM Model 1 and the EM Algorithm lecture of the Johns Hopkins University class on "Machine Translation".

Course web site with slides and additional material:

Textbooks:
  1. Philipp Koehn
  2. machine translation
  3. natural language processing
  4. deep learning
  5. artificial intelligence
  6. MT
Рекомендации по теме
Machine Translation - 0:56:02

Machine Translation - Lecture 4: IBM Model 1 and the EM Algorithm

04. Approaches to 0:04:24

04. Approaches to Machine Translation- RBMT & EBMT

Stanford CS224N NLP 1:18:55

Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 7 - Translation, Seq2Seq, Attention

Machine Translation - 0:54:47

Machine Translation - Lecture 8: Introduction to Neural Networks

Machine Translation - 0:47:20

Machine Translation - Lecture 5: Phrase Based Models

Machine Translation - 0:52:42

Machine Translation - Lecture 1: Introduction

Deep Learning - 0:32:30

Deep Learning - Lecture 9.4 (Natural Language Processing: Neural Machine Translation)

Machine Translation - 0:47:12

Machine Translation - Lecture 12: Neural Translation Model Decoding

Machine Translation - 1:04:51

Machine Translation - Lecture 18: Syntax and Semantics

Learning - Lecture 1:45:49

Learning - Lecture 4 - CS50's Introduction to Artificial Intelligence with Python 2020

Machine Translation - 1:04:12

Machine Translation - Lecture 22: Computer Aided Translation

Machine Translation - 1:04:51

Machine Translation - Lecture 6: Decoding

The impact of 1:12:00

The impact of machine translation on the translation professions

MACHINE TRANSLATION-Artificial Intelligence-NLP-20A05502T-UNIT 0:17:10

MACHINE TRANSLATION-Artificial Intelligence-NLP-20A05502T-UNIT IV-Natural Language for Communication

Neural Machine Translation 0:09:38

Neural Machine Translation Tutorial - An introduction to Neural Machine Translation

Machine Translation - 0:38:45

Machine Translation - Lecture 11: Neural Translation Models

Lecture 10: Neural 1:21:24

Lecture 10: Neural Machine Translation and Models with Attention

Machine Translation - 0:58:46

Machine Translation - Lecture 2: Basics in Language and Probability

Machine Translation 🔥🔥 0:07:03

Machine Translation 🔥🔥

Machine Translation - 0:58:37

Machine Translation - Lecture 15: Words and Morphology

How Large Language 0:05:34

How Large Language Models Work

Machine Translation - 0:52:23

Machine Translation - Lecture 17: Beyond Parallel Data

Lecture 9: Machine 1:20:28

Lecture 9: Machine Translation and Advanced Recurrent LSTMs and GRUs

Machine Translation - 1:08:50

Machine Translation - Lecture 3: Language Models

Комментарии
Автор

35:51

literally crickets in the background lol

appreciate the late night recording bro

dewinmoonl
Автор

Thanks, professor Philipp, very useful lectures. Could you recommend a book/resource on probability/maths that's necessary to follow the lectures for those who's been out of college for a long time?

sheikhakbar
Автор

This is exactly what i was looking for but the audio quality is making it really difficult to follow the explanation. Volume is maxed out but still inaudible at many places.

BizarreKisse
Автор

useless lecture dont waste your time here

amberkhan