What are Embeddings?
Recently, embedding models have been gaining considerable attention in various areas such as natural language processing (NLP), recommender system, knowledge graph completion, etc. This is due to their high accuracy … Read More
Category: Deep Learning
Batch Normalization
Image from https://medium.com/@ilango100/batch-normalization-speed-up-neural-network-training-245e39a62f85 In 2015, a very effective approach (called Batch Normalization) has been proposed to address the vanishing/exploding gradients problems. This learns two parameters to find the optimal scale … Read More
Introduction to Recurrent Neural Networks
Recurrent Neural Networks (RNNs) are a class of neural networks for modeling sequential data such as stock prices, an audio clip, a DNA sequence, a sequence of video frames, a … Read More
4 Approaches to Deal with Vanishing/Exploding Gradients Problems
One of the common problem in deep learning is vanishing gradients problem or exploding gradients problem. It makes hard for lower layers to train. In this post, we will look … Read More