7mins read Term Frequency – Inverse Document Frequency (TF-IDF) is a popular statistical technique utilized in natural language processing and information retrieval […]
17mins read In general, perplexity is a measurement of how well a probability model predicts a sample. In the context of Natural Language Processing, […]
10mins read What do BERT, RoBERTa, ALBERT, SpanBERT, DistilBERT, SesameBERT, SemBERT, SciBERT, BioBERT, MobileBERT, TinyBERT and CamemBERT all have in common? And […]
32mins read This year, we saw a dazzling application of machine learning. The OpenAI GPT-2 exhibited an impressive ability to write coherent and passionate […]
14mins read For decades, Statistical Machine Translation has been the dominant translation model, until the birth of Neural Machine Translation (NMT). NMT is an […]
22mins read In this article, I will be covering the main concepts behind Attention, including the implementation of a sequence-to-sequence Attention model, […]
16mins read Introduction Naïve Bayes algorithm is a supervised classification algorithm based on the Bayes theorem with strong (Naïve) independence among features. In machine learning and data […]
29mins read Sequence-to-sequence models are deep learning models that have achieved a lot of success in tasks like machine translation, text summarization, […]
39mins read Introduction Recurrent Neural Networks (or more precisely LSTM/GRU) have been found to be very effective in solving complex sequence-related problems […]