Neural Network Text Classification Models in TensorFlow
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Updated
Nov 26, 2017 - Python
Neural Network Text Classification Models in TensorFlow
# Machine Learning project 2
Inverstigate different graph embedding algorithms
Modified SVM algorithm called Pegasos implemented with Python
Relation Extraction Competition w/ KLUE Dataset @ Naver Boostcamp AI-Tech
Sentiment analysis with pre trained FastText model, with a Flask API and multiple deploy options in Google Cloud
Experiment tracking and model registry in the NLP project
Recreation of Semantle (a word guessing game that gives the semantic similarity to the secret word) using three pretrained word embeddings: (1) word2vec, (2) GloVe, and (3) fastText
Experiments in the field of Semantic Search using BM-25 Algorithm, Mean of Word Vectors, along with state of the art Transformer based models namely USE and SBERT.
Do some analysis based on main AI conferences
Automated document merging and extractive summarization to take in a search query and provide a crisp version of the news article from over 5 reputed sources. Supported in various languages
sentiment
machine learning with fastText for text classification
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