Simple deep learning
The field of deep learning is vast. The sheer number of publications on the subject is enough to overwhelm anyone. In this series we’ll be taking a step back...
Recent Posts
MNIST extended: a dataset for semantic segmentation and object detection
Most open source datasets for computer vision are huge and complex. Building a model from scratch using ImageNet or Coco is impossible without days of traini...
A simple example of semantic segmentation with tensorflow keras
This post is about semantic segmentation. This is the task of assigning a label to each pixel of an images. It can be seen as an image classification task, e...
The optimal python project structure
In this post, I will describe a python project structure that I have found extremely useful over a wide variety of projects. We’re going to build this struct...
Python logging – A practical guide
Python logging isn’t easy. When I was learning python, I made many attempts to use logging in my applications. Usually I would end up frustrated and thinking...
The 4 streams of deep learning and how to use them successfully
Deep learning and more generally machine learning is a particular paradigm of programming. Rather than telling the computer explicitly each operation it must...
How to use anaconda python effectively
In this article, I will talk about effective use of the Anaconda python distribution and all the tools that come with it. I will use a few commands and post ...
Python development fundamentals
Python is a wonderful language. It’s also incredibly popular in all areas of software development. This popularity is due, in part, to it’s ease of use and a...
Keras implementation of an encoder-decoder for time series prediction using architecture
I created this post to share a flexible and reusable implementation of an encoder/decoder model for time series prediction using Keras.I drew inspiration ...