Gradient Descent with Squared Errors We want to find the weights for our neural networks. Let’s start by thinking about the goal. The network needs to make predictions as close as possible to the real values. To measure this, we use a metric of how wrong the predictions are, the error. Read more…
Introduction So let’s start with two questions, what is deep learning, and what is it used for? The answer to the second question is pretty much everywhere. Recent applications include things such as beating humans in games such as Go, or even jeopardy, detecting spam in emails, forecasting stock prices, Read more…
What is a neural network? The term, Deep Learning, refers to training Neural Networks, sometimes very large Neural Networks. So what exactly is a Neural Network? In this video, let’s try to give you some of the basic intuitions. Let’s start to the Housing Price Prediction example. Let’s say you have a data sets Read more…
The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) spots out some major trends in NLP. This post focus on one exciting and clever paper that motivate the more careful usage of cosine similarity in the word embedding space ” “Correlation Coefficients and Semantic Textual Similarity” [code]” Introduction a Read more…