Tag Archives: Auto Encoder

Variational AutoEncoders and Image Generation with Keras

This article focuses on giving the readers some basic understanding of the Variational Autoencoders and explaining how they are different from the ordinary autoencoders in Machine Learning and Artificial Intelligence. Unlike vanilla autoencoders(like-sparse autoencoders, de-noising autoencoders ..etc), Variational Autoencoders (VAEs) are generative models like GANs (Generative Adversarial Networks). This article is primarily focused on the Variational Autoencoders and… Read More »

Convolutional Denoising Autoencoders for image noise reduction

Autoencoders are unsupervised Deep Learning techniques that are extensively used for dimensionality reduction, latent feature learning (Learning Representations), and also as generative models (Generative Adversarial Networks: GANs). Denoising Autoencoders are slight modifications to the vanilla autoencoders that can be used for reducing noise from real-world noisy datasets. In this tutorial, we will investigate Convolutional Denoising Autoencoders to reduce… Read More »

Autoencoders in Keras and Deep Learning

We all are well aware of the Supervised Machine Learning algorithms where ML algorithm tries to understand the relationship between input features and labels from the training data and is expected to automatically generate a similar kind of relationship between test data features and set of possible output labels. Although we solve lots of problems with supervised learning… Read More »

Python Predicts PUBG Mobile

A simple approach to predict future frames in video (PUBG) data using Python Introduction : It is impossible to predict the future! ( Unless you have a time stone -:) ). But predicting the immediate future is not very hard for us (Humans). We do it in the real-life quite often — while playing a game or watching a movie one can… Read More »

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