@@ -47,7 +47,7 @@ Basic knowledge of Python programming language
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@@ -47,7 +47,7 @@ Basic knowledge of Python programming language
|[Practical_09_The_Role_Of_Machine_Learning_In_NLP.ipynb][09]| Supervised and unsupervised machine learning and its NLP applications |
|[Practical_09_The_Role_Of_Machine_Learning_In_NLP.ipynb][09]| Supervised and unsupervised machine learning and its NLP applications |
|[Practical_10_Sentiment_analysis.ipynb][10]| Sentiment analysis (VADER, sklearn, Random Forest Classifier, neural networks)|
|[Practical_10_Sentiment_analysis.ipynb][10]| Sentiment analysis (VADER, sklearn, Random Forest Classifier, neural networks)|
|[Practical_11_Unsupervised_Learning_and_Topic_modeling.ipynb][11]| Unsupervised machine learning and topic modelling |
|[Practical_11_Unsupervised_Learning_and_Topic_modeling.ipynb][11]| Unsupervised machine learning and topic modelling |
|[Practical_13_NLP_Ethics.ipynb][13]| NLP ethics (big data dangers, gender and racial bias, green NLP, privacy, crowdsourcing, text generation (GPT-2, GPT-3), chatbots |
|[Practical_12_NLP_Ethics.ipynb][13]| NLP ethics (big data dangers, gender and racial bias, green NLP, privacy, crowdsourcing, text generation (GPT-2, GPT-3), chatbots |