Feed forward networks cannot learn from the past, but Recurrent Neural Networks (RNNs) can learn by accepting data in a sequence. Examples of applications for RNNs include the text autocomplete feature on your phone and performing language translations. Recurrent Neurons (RNs) act as the building blocks of RNNs. The difference between RNs and feed forward […]
Fastai’s Practical Deep Learning for Coders Course Release – 2020 Update!
On Aug 21st, 2020, fastai released a new version of their Practical Deep Learning for Coders -Part 1 course. This course is a must-take for new and intermediate deep learning practitioners. It is well done and teaches you intuition without drowning you in theory. The only prerequisites are some high-school math, and a year of […]
How Genetic Algorithms Work
Genetic algorithms (GAs) are inspired by biology where only the fittest genes survive. It is based on Charles Darwin’s Natural Selection theory. We start with 2 parent chromosomes that each contain an ordered set of genes. Each parent contributes some of their genes when they mate to create children chromosomes. There is a randomness to […]
Regression & Classification Models in PyTorch
The purpose of this article is to share what I learned from a recent PyTorch course. We will share general machine learning tips as well as insights specific to deep learning library PyTorch. PyTorch is a deep learning library for Python and was created by Facebook in 2016. PyTorch is good for deep learning beginners. […]