1. Objective The goal is to build a complete Deep Learning application, including: -Training a sentiment analysis model. -Saving the…
ARTIFICIAL INTELLIGENCE (23) – Natural Language Processing (4) Text Representations in NLP (3) Word embeddings
Word embeddings are a more advanced way to represent words compared to count vectors. Instead of just counting words, each…
ARTIFICIAL INTELLIGENCE (22) – Natural Language Processing (3) Text Representations in NLP (2) Count vectorizer
A Count Vectorizer is a way for a computer to understand a sentence by counting words instead of looking at…
ARTIFICIAL INTELLIGENCE (21) – Natural Language Processing (3) Text Representations in NLP (1) One-hot encoding
We are going to explore the inputs representations in the process of transforming a text corpus into different input formats…
ARTIFICIAL INTELLIGENCE (20) – Natura Language Processing (2) Embeding Lab
I think the best way to start talking about embeddings is to propose a Lab about it. In the next…
ARTIFICIAL INTELLIGENCE (19) – Natural Language Processing (1) Byte Pair Encoding: A Powerful Subword Tokenization Method in Modern NLP
Processing human language remains one of the most intricate challenges in artificial intelligence. While humans communicate through words, nuance, and…
yolandamuriel.com 
Debe estar conectado para enviar un comentario.