In the afternoon I noticed that the Psalmopoeus irminia sling I keep had molted; I saw the exoskeleton on top of a piece of moss coming out of the cork tube it lives in.
I hadn't seen the spider for weeks, and at times I was worried it had passed away. However, 4 days ago I removed some moss from it's cork tube and I saw legs that moved. And today it had kicked out it's exuviae.
The previous molt was discovered the 26th of May, 2020.
In a neural network, the activation function is responsible for transforming the summed weighted input from the node into the activation of the node or output for that input.
The rectified linear activation function is a piecewise linear function that will output the input directly if it is positive, otherwise, it will output zero. It has become the default activation function for many types of neural networks because a model that uses it is easier to train and often achieves better performance.
In this tutorial, you will discover the rectified linear activation function for deep learning neural networks.
Source: A Gentle Introduction to the Rectified Linear Unit (ReLU), an article by Jason Brownlee.
I used to be afraid of async Rust. It's easy to get into trouble!
But thanks to the work done by the whole community, async Rust is getting easier to use every week. One project I think is doing particularly great work in this area is async-std.
Source: Surviving Rust async interfaces.