some notes on how to train a Deep Learning model using Keras' Sequential API
Draft: this article is a draft, its content will change.
Keras Sequential API (KSA) allows to easily create Deep Learning networks that are made of a sequence of stack of layers. The nice thing about KSA is that we only have to provide the model with the input shape of our data and Keras will take care of managing the shapes of . . .
DRAFT: so far jupyterhub works only through http. I'll add steps on how to use https, and some other tweaks to the configuration.
First of all let's create an Amazon Instance.
For this tutorial I set up a t2.micro instance based on Ubuntu 18.04 64 bit.
I would like to access jupyterhub from remote locations . . .
I recently got involved in a project requiring the use of an OCR (Optical Character Recognition) to extract text from images. After a bit of research, we decided to use Google's Tesseract.
In particular we decided to go for version
3.0.5 due to the possibility to save the output in a nicely formatted tsv file containing, among . . .