Machine Learning (ML) Applications of NLP: Extraction from PDF, Language Translation and more In this, we have explored core NLP applications such as text extraction, language translation, text classification, question answering, text to speech, speech to text and more.
Machine Learning (ML) Applications of NLP: Text Generation, Text Summarization and Sentiment Analysis In this article, we have explored 3 core NLP applications such as Text Generation using GPT models, Text summarization and Sentiment Analysis.
Machine Learning (ML) Different core topics in NLP (with Python NLTK library code) In this, we have covered different NLP tasks/ topics such as Tokenization of Sentences and Words, Stemming, Lemmatization, POS Tagging, Named Entity Relationship and more.
Machine Learning (ML) XLNet, RoBERTa, ALBERT models for Natural Language Processing (NLP) We have explored some advanced NLP models such as XLNet, RoBERTa and ALBERT and will compare to see how these models are different from the fundamental model i.e BERT.
Machine Learning (ML) LSTM & BERT models for Natural Language Processing (NLP) The fundamental NLP model that is used initially is LSTM model but because of its drawbacks BERT became the favored model for the NLP tasks.
Machine Learning (ML) The Idea of Indexing in NLP for Information Retrieval We have explored the fundamental ideas for Information Retrieval that is Indexing Data. We have covered various types of indexes like Term document incidence matrix, Inverted index, boolean queries, dynamic and distributed indexing, distributed indexing and Dynamic Index.
Machine Learning (ML) Heaps' law in NLP for Frequency of Words Heap's Law in NLP is a relation between the number of unique words to the total number of words in a document. It is, also, known as Herdan's law.
Software Engineering Basic Bits hacks in Python We have covered several basic bit hacks in Python which everyone should know to write optimized code. Tricks include find sign of an integer, negate an integer and more.
