Nesse repositório contém os arquivos de notebook e datasets usados para o trabalho de avaliação continuada na Facens para a matéria de Inteligência Artificial.
Nessa avaliação continuada, será tratado o problema de classificação de texto, e mais especificamente, classificar mensagens de Spam.
O dataset usado nesses experimentos foram obtidos do Kaggle e você pode visualizar clicando aqui.
Os notebooks foram divididos em métodos, e cada um, resolve o mesmo problema usando um método diferente.
Abaixo, você pode visualizar as informações de cada notebook criado:
- Vinícius Lourenço Claro Cardoso (180618)
- https://medium.com/@datamonsters/text-preprocessing-in-python-steps-tools-and-examples-bf025f872908
- https://www.devmedia.com.br/html-entities-html-symbols-html-characters/1011
- https://stackoverflow.com/questions/20186344/ipynb-import-another-ipynb-file
- https://gist.github.com/H4ad/e4c5f79849eebdec32b655d7bba6be0a
- https://www.kaggle.com/team-ai/spam-text-message-classification
- https://www.youtube.com/watch?v=oLane_Vh3CU
- https://stackoverflow.com/questions/50382248/how-can-i-import-one-jupyter-notebook-into-another
- https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Perceptron.html
- http://computacaointeligente.com.br/outros/intro-sklearn-part-3/
- http://computacaointeligente.com.br/conceitos/avaliando-performance-cross-validation/
- https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html#
- https://towardsdatascience.com/deep-neural-multilayer-perceptron-mlp-with-scikit-learn-2698e77155e
- https://numpy.org/doc/stable/reference/generated/numpy.concatenate.html
- https://docs.w3cub.com/scikit_learn/modules/generated/sklearn.neural_network.mlpclassifier#sklearn.neural_network.MLPClassifier.fit
- https://en.wikipedia.org/wiki/Quasi-Newton_method
- https://machinelearningmastery.com/rectified-linear-activation-function-for-deep-learning-neural-networks/
- https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html
- https://machinelearningmastery.com/how-to-prepare-categorical-data-for-deep-learning-in-python/