Machine Learning

Word2Vec is a popular natural language processing technique that is used to create high-quality vector representations of words from large datasets of text. It is a neural network based model that is capable of capturing the semantic and syntactic meaning of words, and it has been widely used in various downstream NLP tasks such as text classification, sentiment analysis, and machine translation.

Feature Scaling is a small but very important component in any Machine Learning or Data Science project. Even though we are using feature scaling in our day-to-day development processes, sometimes we are not very much clear about the underline concepts and limitations of different types of feature scaling. In this blog post we discuss concepts like what is feature scaling?, why do we need feature scaling?