What is the purpose of using embeddings in text classification with TensorFlow?
Saturday, 05 August 2023
by EITCA Academy
Embeddings are a fundamental component in text classification with TensorFlow, playing a crucial role in representing textual data in a numerical format that can be effectively processed by machine learning algorithms. The purpose of using embeddings in this context is to capture the semantic meaning and relationships between words, enabling the neural network to understand
- Published in Artificial Intelligence, EITC/AI/TFF TensorFlow Fundamentals, Text classification with TensorFlow, Designing a neural network, Examination review
Tagged under:
Artificial Intelligence, Embeddings, Neural Networks, TensorFlow, Text Classification, Word2Vec
What are word embeddings and how do they help in extracting sentiment information?
Saturday, 05 August 2023
by EITCA Academy
Word embeddings are a fundamental concept in Natural Language Processing (NLP) that play a crucial role in extracting sentiment information from text. They are mathematical representations of words that capture semantic and syntactic relationships between words based on their contextual usage. In other words, word embeddings encode the meaning of words in a dense vector
- Published in Artificial Intelligence, EITC/AI/TFF TensorFlow Fundamentals, Natural Language Processing with TensorFlow, Training a model to recognize sentiment in text, Examination review
Tagged under:
Artificial Intelligence, GloVe, Natural Language Processing, Sentiment Analysis, Word Embeddings, Word2Vec