logistic-regression
- Maximum Entropy Markov Models and Logistic Regression (12 Nov 2017)
This blog post is an introduction to Maximum Entropy Markov Model, it points out the fundamental difference between discriminative and generative models, and what are the main advantages of the Maximum Entropy Markov Model over the Naive Bayes model.
viterbi sequence-prediction scikit-learn pos-tags conditional-random-fields NER word2vec word-embeddings triplet-loss syntactic-dependencies sentence-transformers relationship-extraction neural-networks fine-tuning evaluation_metrics embeddings coursera conference SyntaxNet NLTK LSTM CRF wikidata transformers tokenization tf-idf text-summarisation semantic-web resources reference-post production portuguese political-science named-entity-recognition naive-bayes multi-label-classification monitoring mlops maximum-entropy-markov-models logistic-regression llms language-models information-extraction imbalanced_data hyperparameter-optimization hidden-markov-models grid-search gensim generative-ai fasttext document-classification doc2vec deployment dependency-graph dataset data-challenge convolutional-neural-networks contrastive-learning classification books attention SPARQL RNN PyData KOVENS GRU