About loss and loss functions
When you’re training supervised machine learning models, you often hear about a loss function that is minimized; that must be...
Category: Other ML techniques
Intuitively understanding SVM and SVR
There is a lot of interest in deep learning models today: deep neural networks show beyond-average performance on many tasks,...
Creating an MLP for regression with Keras
Machine learning is a wide field and machine learning problems come in many flavors. If, say, you wish to group...
How to create a basic MLP classifier with the Keras Sequential API
In one of my previous blogs, I showed why you can’t truly create a Rosenblatt’s Perceptron with Keras. Fortunately for...
Why you can’t truly create Rosenblatt’s Perceptron with Keras
…and what to do about it! It was January 1957 when a report was released by Cornell Aeronautical Laboratory. It...
Linking maths and intuition: Rosenblatt’s Perceptron in Python
According to Wikipedia, Frank Rosenblatt is an “American psychologist notable in the field of artificial intelligence”. And notable, he is....
Commoditizing AI? The state of automated machine learning.
It cannot go unnoticed that machine learning has been quite the hype these past few years. AI programs at universities...
Can neural networks approximate mathematical functions?
In the paper Multilayer feedforward networks are universal approximators written by Kurt Hornik, Maxwell Stinchcombe and Halbert White in 1989,...
Could chaotic neurons reduce machine learning data hunger?
This week, I found a very interesting work on Arxiv that was published only a short while ago. It’s called...
