GitHub - Robert-E-630/Classifying_Sentence_Toxicity: NLP Project - Sentence Classification - Toxicity- Approx 20,000 comments - ranging from 2 to 30 words. Balanced Data Set. 1. Traditional, pre-2010 NLP and ML techniques used. 2. Dense Word Vectors - w2v & Glove, sentence vector created from averaged word vectors, ANN. 3. Glove combined with bi-LSTMs and 2D Convs.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
Classifying Toxicity - ANN and Sentence Embeddings from Word Vector Avgs - 768D Glove - Dec 21st.ipynb		Classifying Toxicity - ANN and Sentence Embeddings from Word Vector Avgs - 768D Glove - Dec 21st.ipynb
Classifying Toxicity - Classical ML - Dec 25th.ipynb		Classifying Toxicity - Classical ML - Dec 25th.ipynb
Classifying Toxicity - bi-LSTMs and 2D Convs - 200D Glove and 30 sequence Sentences - Dec 21st.ipynb		Classifying Toxicity - bi-LSTMs and 2D Convs - 200D Glove and 30 sequence Sentences - Dec 21st.ipynb
remove_stop_words Classifying Toxicity - ANN and Sentence Embeddings from Word Vector Avgs - 768D Glove - Dec 21st - Copy.ipynb		remove_stop_words Classifying Toxicity - ANN and Sentence Embeddings from Word Vector Avgs - 768D Glove - Dec 21st - Copy.ipynb
submission.csv		submission.csv
tox_y_test		tox_y_test

About

NLP Project - Sentence Classification - Toxicity- Approx 20,000 comments - ranging from 2 to 30 words. Balanced Data Set. 1. Traditional, pre-2010 NLP and ML techniques used. 2. Dense Word Vectors - w2v & Glove, sentence vector created from averaged word vectors, ANN. 3. Glove combined with bi-LSTMs and 2D Convs.