Create a Neural Network With PyTorch

PyTorch is an Artificial Intelligence library that has been created by Facebook's artificial intelligence research group . The source code is accessible...

Deep Learning with Keras – Part 7: Recurrent Neural Networks

Intro In this part of the series, we will introduce Recurrent Neural Networks aka RNNs that made a major...

AI and Data Science Tools on Amazon Web Services

As the leading cloud provider, Amazon Web Services offers numerous tools for a variety of applications. The sheer number of offerings can...

Deep Learning with Keras – Part 6: Textual Data Preprocessing

Intro Congratulations for going far in this Keras tutorial. After working with numeric, categorical and image data, it is...

How Artificial Intelligence Supports Human Intelligence in Business

In June, researchers at MIT and Brown University revealed their latest creation: Northstar. The system uses artificial intelligence (AI) and machine learning...

Introduction to Image Classification using Pytorch to Classify FashionMNIST Dataset

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.

Building a Feedforward Neural Network using Pytorch NN Module

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

Logistic Regression With A Real-World Example in Python

In this tutorial, You’ll learn Logistic Regression. Here you’ll know what exactly is Logistic Regression and you'll also see an Example...

Getting Started With Pytorch In Google Collab With Free GPU

In this post, we will discuss the basics of pytorch by using the google colab gpu

How Generative Adversarial Networks (GANs) work?

Generative Adversarial Networks were first introduced in 2014 in a research paper. They have also been called  “the most interesting idea in...