### Light on Math Machine Learning: Intuitive Guide to Understanding Word2vec

Here comes the third blog post in the series of light on math machine learning A-Z. This article is going to be about Word2vec algorithms. Word2vec algorithms output word vectors. Word vectors, underpin many of the natural language processing (NLP) systems, that have taken the world by a storm (Amazon...

### Neural Machine Translator with 50 Lines of Code + Guide

Jupyter Notebook for this Tutorial: Here Recently, I had to take a dive into the seq2seq library of TensorFlow. And I wanted to a quick intro to the library for the purpose of implementing a Neural Machine Translator (NMT). I simply wanted to know “what do I essentially need to...

### Make CNNs for NLP Great Again! Classifying Sentences with CNNs in Tensorflow

Tensorflow Version: 1.2 Original paper: Convolution Neural Networks for Sentence Classification Full code: Here RNN can be miracle workers, But… So, you’re all exhausted from trying to implement a Recurrent Neural Network with Tensorflow to classify sentences? You somehow wrote some Tensorflow code that looks like a RNN but unable...

### GloVe: Global Vectors for Word Representation + Implementation

Hi, This post will be about a new Word2Vec technique that has come after skip-gram and CBOW, introduced in this paper. Why the authors claim that GloVe is better than context-window based methods is that, it tries to combine both global and local statistics in order to create more general...

### Word2Vec (Part 2): NLP With Deep Learning with Tensorflow (CBOW)

This is a continuation from the previous post Word2Vec (Part 1): NLP With Deep Learning with Tensorflow (Skip-gram). But in this one I will be talking about another Word2Vec technicque called Continuous Bag-of-Words (CBOW). Intuition CBOW So what exactly is CBOW? CBOW, or continuous bag-of-words is conceptually similar to a...

### Word2Vec (Part 1): NLP With Deep Learning with Tensorflow (Skip-gram)

G’day, I will be writing about 2 popular techniques for converting words to vectors; Skip-gram model and Continuous Bag of Words (CBOW). These are unsupervised learning methods to learn the context of words. This post is structured as follows. First I’ll talk about the motivation for Word2Vec techniques. Next I...