Deep Learning

OpenAI’s gradient checkpointing: A package that makes huge neural nets fit into memory

OpenAI releases a python/Tensorflow package, Gradient checkpointing! Gradient checkpointing lets you fit 10x larger neural nets into memory at the…

2017 Generative Adversarial Networks (GANs) Research Milestones

Generative Adversarial Models, introduced by Ian Goodfellow, are the next big revolution in the field of deep learning. Why? Because…

How to Implement a Neural Network with Single-Layer Perceptron

In this article we help you go through a simple implementation of a neural network layer by modeling a binary…

2 ways to customize your deep learning models with Keras

Keras has a lot of built-in functionality for you to build all your deep learning models without much need for…

DeepMind introduces NarrativeQA: A real-world dataset for testing the limits of Reading Comprehension

DeepMind introduces NarrativeQA, a data repository setup for understanding complex narratives. Reading comprehension (RC)—in contrast to information retrieval—requires integrating information…

How to Install Keras on Docker and Cloud ML

Keras is a deep learning library which can be used on the enterprise platform, by deploying it on a container.…

AI learns to talk naturally with Google’s Tacotron 2

Google has been one of the leading forces in the area of text-to-speech (TTS) conversions. The company has further leaped…

Google introduces NIMA: A Neural Image Assessment model

Google recently introduced NIMA (Neural Image Enhancement Model), a deep convolutional neural network. NIMA is trained to predict which images…

Behind the scenes: Deep learning evolution and core concepts

This article will take you through the history of Deep learning and how it has grown over time. It will…

Deep Learning Algorithms: How to classify Irises using multi-layer perceptrons

From our below given post, we help you learn how to classify flower species from Iris dataset using multi-layer perceptrons.…