In this post, we cover the essential elements required for training Neural Networks for an image classification problem. We will still treat the internal network architecture as a black box so that we ...
Tensorflow & Keras Tutorial: Linear Regression
Before studying deep neural networks, we will cover the fundamental components of a simple (linear) neural network. We'll begin with the topic of linear regression. Since linear regression can be ...
Object detection with depth measurement using pre-trained models with OAK-D
This is the third blog post in the Oak series. If you haven't checked out the previous posts on OAK, check them below. In this post, we are going to look at how we can run an existing pre-trained ...