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In the previous post, we learned Word Embedding. In this post, we learn Sentence Embedding and Document Embedding. In the previous post, we learned word embeddings i.e. for the smallest units in language word. However,
Continue readingIn this post, we learn Word Embedding briefly. Word Embeddings Introduction In simple understanding, Word Embeddings are vector representations of a word. In physics, Scalar means a value or physical quantity. In Latin, Vecotr means
Continue readingIn all the previous posts, we have learned about NLP Models, Classifiers, and evaluating the NLP classifiers. In this post, we learn a new topic and it is Feature Selection in NLP Text processing. Introduction
Continue readingIn the previous posts, we learned various classifiers. In this post, we discuss how to evaluate those classifiers. Why do we Evaluate Classifiers? After you develop a machine learning model based on training data, you
Continue readingIn the previous post, we discussed the Naive Bayes Probabilistic classifier. In this post, we learn Linear classifiers. Firstly, Linear means a straight line. Fundamental Concept in Linear Probabilistic Classifer In Linear classifiers, we consider
Continue readingIn the previous post, we learned what are probabilistic classifiers definition. In this post, we introduce Simple Classifiers like Naive Bayes and in the next post we introduce Linear classifiers. These two are probabilistic classifiers.
Continue readingIn the previous post, we learned the classifier definition. In this post, we learn the definition of Probabilistic Classifiers and in the next post, we learn Naive Bayes and Linear classifiers. These two are probabilistic
Continue readingIn all the previous posts we discussed foundational concepts of NLP and Language Models. In this post, we introduce Classifiers in Language Models. Classifiers Definition in Simple Terms In simple terms, a classifier is a
Continue readingIn the previous posts, we discussed various foundational topics related to NLP and Language Models. In this topic, we discuss NLP key terms and concepts. With all the knowledge we obtained through previous posts and
Continue readingIn the previous post, Regularization Techniques in Machine Learning are discussed. In this post, we discuss the Smoothing Regularization technique for NLP Language Models. Quick Review of Regularization Technique – Regularization technique prevents the overfitting
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