What are Transformers? Transformers are new state-of-the-art deep learning architectures used for Natural Language Processing(NLP). What is NLP? NLP comprises of AI tasks related to text process...

Contingency table Contingency table and chi squared distributions are used to determing if two categorical varibles are independent or not. For example: The following table shows a contingency tab...

Original Documentation Video link: https://channel9.msdn.com/Events/Connect/Microsoft-Connect–2018/D240/ Start by creating a free subscription in azure portal : https://portal.azure.com Create wo...

This is a GRU based RNN classifier to predict the read probability of a user from his/her email data. import torch import pandas as pd import numpy as np from torch.utils.data import Dataset,DataL...

#! pip install pytorch-pretrained-bert Using BERT BERT Paper Tokenizer See how BERT tokenizer works Tutorial source : Huggingface BERT repo import torch from pytorch_pretrained_bert import Bert...

A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle. This is a complete example of an RNN multiclass classifier in pytorc...

Word Embeddings Word embeddings are lower dimentional dense representation of words. Generally, embeddings are generated using semi supervised learning where the embeddings are learned based on an...

Convolution Convolution is the building block of Convolutional Neural Networks (CNN). CNNs are used both for image and text processing. Online diagrams do a great job explaining CNNs. I, however f...

Deep learning Functions Functions in this notebook are created using low level math functions in pytorch. Then the functions are validated with preimplemented versions inside pytorch. import torc...

Quickstart Install a full Ruby development environment Install Jekyll and bundler gems gem install jekyll bundler bundle add jekyll-sitemap bundle install...