Data Science

Recurrent Neural Networks(RNN) are a type of Neural Network where the output from the previous step is fed as input to the current step. In the case of Convolution Neural Networks (CNN), the output from the softmax layer in the context of image classification is entirely independent of the previous input image.

One of the capabilities of deep learning is image recognition, The “hello world” of object recognition for machine learning and deep learning...

After four years of hard work by Kevin Moore and Aneesh Karve (Founders), Quilt Data comes live from stealth mode. This platform can be...

SuperDataScience Learning Machines 101 IBM Analytics Insights Talking Machines

In this blog post, we will discuss how to build a Convolution Neural Network that can classify Fashion MNIST data using Pytorch on Google Colaboratory. The way we do that is, first we will download the data using Pytorch DataLoader class and then we will use LeNet-5 architecture to build our model. Finally, we will train our model on GPU and evaluate it on the test data.

In this blog post, we will discuss how to perform exploratory data analysis by creating awesome visualizations using matplotlib and seaborn by taking a real-world data set.

Motivation In the previous articles, we solved problems with numeric and categorical data, and we learned the different transformations...

Feedforward neural networks are also known as Multi-layered Network of Neurons (MLN). These network of models are called feedforward because the information only...

Regression After two introductory tutorials, its time to build our first neural network! The network we are building solves...

Link to Part 1. Dealing with Data Motivation Training deep...