In this post, we will learn about Convolutional Neural Networks (CNN) in the context of an image classification problem. We first cover the basic structure of CNNs and then delve into the detailed ...
Implementing a CNN in TensorFlow & Keras
In this post, we’ll learn how to implement a Convolutional Neural Network (CNN) from scratch using Keras. Here, we show a CNN architecture similar to the structure of VGG-16 but with fewer layers. We ...
Tensorflow & Keras Tutorial: Linear Regression
Before studying deep neural networks, we will cover the fundamental components of a simple (linear) neural network. We'll begin with the topic of linear regression. Since linear regression can be ...
t-SNE: T-Distributed Stochastic Neighbor Embedding Explained
Visualizing training data is often essential to design a good Machine Learning model. However, generally feature dimensions are much more than three. So to get visual insight, dimensionality reduction ...
Variational Autoencoder in TensorFlow
Deep Learning has already surpassed human-level performance on image recognition tasks. On the other hand, in unsupervised learning, Deep Neural networks like Generative Adversarial Networks ( GANs ) ...
Autoencoder in TensorFlow 2: Beginner’s Guide
Imagine you have an image or an audio file which you would like to transfer to a friend. Sending the raw format data could be time-consuming and potentially inefficient, especially when the files' ...
