Machine learning and natural language processing
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Machine learning and natural language processing
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Nyní studovat1 Course overview, project assignment overview. Overview of text pre-processing
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Nyní studovat2 ML techniques for NLP 1
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Nyní studovat3 Distributional semantics, LSA, word embeddings
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Nyní studovat4 Ne moc. Dis ease
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Nyní studovat5 ML techniques for NLP 2. Text clustering.
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Nyní studovat6 ML for NLP III: Recurrent NN. Outliers in text I.
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Nyní studovatIndependent Czechoslovak State Day
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Nyní studovat8 LSTM. RNN/LSTM case studies. ILP
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Nyní studovat9 Poster session
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Nyní studovat10 Learning language in logic. Keyness. Summarization
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Nyní studovat11 Sentiment analysis (including lexicons of “sentiment words”)
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Nyní studovat12 Machine learning for knowledge extraction from text
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Independent Czechoslovak State Day
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Machine learning and natural language processing
-
Nyní studovat1 Course overview, project assignment overview. Overview of text pre-processing
-
Nyní studovat2 ML techniques for NLP 1
-
Nyní studovat3 Distributional semantics, LSA, word embeddings
-
Nyní studovat4 Ne moc. Dis ease
-
Nyní studovat5 ML techniques for NLP 2. Text clustering.
-
Nyní studovat6 ML for NLP III: Recurrent NN. Outliers in text I.
-
Nyní studovatIndependent Czechoslovak State Day
-
Nyní studovat8 LSTM. RNN/LSTM case studies. ILP
-
Nyní studovat9 Poster session
-
Nyní studovat10 Learning language in logic. Keyness. Summarization
-
Nyní studovat11 Sentiment analysis (including lexicons of “sentiment words”)
-
Nyní studovat12 Machine learning for knowledge extraction from text
-