My submission for the Innoplexus Challenge 2018. It contains code and intermediate files.
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Updated
Aug 19, 2018 - Python
My submission for the Innoplexus Challenge 2018. It contains code and intermediate files.
Classe responsável por simplificar o processo de criação de um modelo Doc2Vec (gensim) de forma simples, sem muita configuração. Dicas usando elasticsearch e singlestore.
Document searching from queries using Inverted index
Semantic Classification of OERs with Word Embeddings
Addressing Political Bias in News Articles with Multinomial Regression
筑波大学シラバスデータを用いて科目概要を Doc2Vec でベクトル化し、類似した科目を表示する
Topic modeling on tweets. Using doc2vec word embedding and k-means clustering to categorize tweets.
Inverted index and Positional index for a set of collection to facilitate Boolean Model of IR. Inverted files and Positional files are the primary data structure to support the efficient determination of which documents contain specified terms and at which proximity.
Ce fut mon prémier projet NLP où j'ai réalisé la détection de spam en utilisant les algorithmes d'embedding pour encorder mes textes. J'ai utilisé Random Forest et Milti-Layres Perceptrons pour la phase de classification. Ce qui a pemit l'obtension des précisions respective de 97% et 98%. J'ai aussi appris à documenter mes codes via sphinx
Code for analyzing hate speech tweets using Wikipedia-based contextual representations.
We save all the R&D we have done for Recommendation System and Neo4j
Doc2Vec and Annotated Lyrics: Are they "Genius"? (DSI Capstone II Project)
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