Gradient Descent is one of the most fundamental optimization techniques used in Machine Learning. But what is a gradient? On what do we descent down and what do we even optimize in the first place? Those might be some of the questions which come to mind when having the first encounters with Gradient Descent. Let's … Continue reading Gradient Descent from Scratch
Deep learning systems are able to learn extremely complex patterns, and they accomplish this by adjusting their weights. How are the weights of a deep neural network adjusted exactly? They are adjusted through a process called backpropagation. Without backpropagation, deep neural networks wouldn’t be able to carry out tasks like recognizing images and interpreting natural … Continue reading What is Backpropagation?
Are you trying to predict time series but don't know where to start? This blog post will provide a comparison of the most prominent techniques and show you how to implement them. Business Problem Time Series prediction can be used in a number of business areas. You can think of a number of areas and … Continue reading A short introduction to Time Series
Here’s something that might surprise you: neural networks aren’t that complicated! The term “neural network” gets used as a buzzword a lot, but in reality they’re often much simpler than people imagine. This post is intended for complete beginners and assumes ZERO prior knowledge of machine learning. We’ll understand how neural networks work while implementing … Continue reading An Introduction to Neural Networks