Machine Learning
d, patented, and published Word2Vec in two publications in 2013. For learning word embeddings from raw text, Word2Vec is a computationally efficient predictive model. Continue reading
For calculating the word embeddings, intuition has been used that word’s meaning should be represented by the words that frequently appear nearby that word. intuition has been used that word’s meaning should be represented by the words that frequently appear nearby that word. In SVD based embedding methods, first, we create the matrix of co-occurrence, then we reduce the dimensionality of the matrix using SVD to get the embeddings. Continue reading
In word embeddings, each word can be represented as an N-dimensional vector (mostly 300), and similarity between two words can be calculated by calculating the distance between these words in N-dimensional space. So, it solves the high dimensionality-related issues as well, which we have seen in One-Hot-Encoding. Continue reading
One of the simplest forms of word representation in NLP is One-Hot-Encoding. It requires very little computing power to convert text data into one-hot encoding data, and it’s easy to implement. Continue reading
To overcome the limitation of common words in the Bag of Word (BOW) methodology, a technique called TF-IDF (Term Frequency- Inverse Document Frequency) has been created. It gives the importance of any term in a document if it is occurring multiple times in that document, and also penalize the importance of a term in a document in case it is occurring very frequently in various documents in the corpus. Continue reading
In NLP, The Bag-of-Words model is useful in Search, Recommendation, Classification, etc. use cases. This model uses Label/ Integer word encoding. The Bag-of-Words model counts the occurrence of each word within a document. The count can be considered as the weightage of a word in a document. Based on the… Continue reading
Label/ Integer Encoding of Words is one of the initial methodologies used to encode the words into numerical data. In this methodology, we assign a numerical value to every word in the corpus starting with zero. Continue reading
NLP is a field of linguistics, computer science, and artificial intelligence. It helps computers understand, interpret and manipulate human language. NLP is commonly used in speech recognition, natural language understanding, and natural language generation. It helps computers to understand natural language in order to perform some tasks. Continue reading