The first task we need to complete in any NLP-based analysis or model training is to convert the words into vectors. There are many ways of converting documents to vectors. Some of the most common techniques, like One hot encoding, Count Vectorizer, TF-IDF, and word embeddings, are discussed here... Read more.
Word2Vec was one of the biggest leaps in the field of Natural Language Processing when it was introduced by Google researchers in 2013. Here is a small description of what led to the creation of word2vec models and how is it created. Read more.
Zero Knowledge Proof provides you with a way of proving your claim without providing any data additional data for the proof. Learn how this can be used to protect your data online. Read more.
This time Rohit Sharma is under analysis, with his recent form in the South Africa and in general for the past year. Click the heading to read more. Read more.
