Project Overview / Problem Introduction As part of this project, a Convolutional Neural networks (CNNs) is trained that processes real-world, user-supplied images to identify if it contains a dog or a human face and then predict the closest breed the dog or the human face resembles with. Typically, CNNs are deep neural networks that require…

Is technology the same as in 2011 or do we need to update ourselves? Are there currently more women in our industry compared to 2011? Where do most developers live? In order to gain an understanding of how the technology industry is changing, we examined data StackOverflow developer's survey data…

In the previous article, we briefly touched upon the problem of “Vanishing and Exploding gradients”, especially when dealing with longer sequences. In this article, one strategy termed “selectively read, selectively write and selectively forget” is discussed that would help to deal with the problem of vanishing and exploding gradients In…

In the last article, we discussed the loss function jar for Sequence-based problems. In this article, details about the learning algorithm are discussed: Learning Algorithm One question at this point would be “can the gradient descent algorithm be used in the context of a recurrent neural network?” The standard recipe that is…

In the last article, we discussed the Data Modeling jar for Sequence labeling and sequence classification problems. In this article, we touch upon the loss function the sequence-based problems Loss Function Sequence Classification Task Let’s say there are “2 classes positive and negative” and in this case (snippet below), the “actual label…

In the last article, we discussed the Data and Task jar for Sequence labeling problems. In this article, we touch upon the data modeling aspect for Sequence classification and sequence labeling problems Data Modeling A model is an approximation of the true relationship that exists between the input and the output. And…

In the last article, we discussed the Data and Task jar for Sequence classification-specific problems. In this article, we touch upon the Data and Task jar for Sequence labeling problems Data and Tasks for Sequence Labeling Let’s first discuss the objective of Sequence Labeling — Here, for every word in the input sentence, the model predicts…

In the last article, we touched upon the base of RNNs and discussed how RNNs inherently covers all the desired properties of an ideal network to address sequence-based problems

How to model sequence learning problems? In the previous article, we looked at the base and properties of sequence learning problems, and some examples of sequence learning problems in NLP, video, and speech data. In this article, let’s dive into the details of the modeling aspect of sequence-based problems Let’s consider the task of character prediction…