Found this great article which covers all the big components - recommended reading!

# The mechanics of a simple neural network

Learn from your mistakes! This is my personal 'cheat sheet' on common concepts you'll encounter on your deep learning journey! My goal was to create a 2-page at-a-glance document that could serve as a reminder on how each component of a neural network works and how each fits into the bigger picture. It isn't designed... Continue Reading →

There are very few mailing lists that I remain subscribed to AND faithfully open on a regular basis. But Analytics Vidhya always has something interesting, something complicated explained simply, a step-by-step tutorial... Take, for example, the article I received this morning 10 matplotlib tricks - I so totally need this - it seems like a... Continue Reading →

# AnalyticsVidhya ♥︎

# Visualizing data overlaps

An example use case is this: you have a list of customers who have bought the various products that you sell. You want to know where the overlaps are, for example: How many customers who bought the Blue Widget also bought the Green Widget? Or what percentage of customers who bought the Blue Widget also... Continue Reading →

# Calculus rules to live by

Calculus is a big topic, but by and large, there are quite specific aspects of calculus that come into machine learning and in particular deep learning algorithms. This article is not intended to explain how and why things are as they are; rather it's my own personal cheat sheet for when I need to remember... Continue Reading →

# PyTorch Lightning – Regression Example

I find there are a lot of tutorials and toy examples on convolutional neural networks - so many ways to skin an MNIST cat! - but not so many on other types of scenarios. So I've decided to put together a quick sample notebook on regression using the bike-share dataset. After learning the basics of neural... Continue Reading →

# Dream come true

Sometime in 2017, I started this crazy journey... I finally knew what I wanted to be when I was big: a data scientist! It's funny how, having this very clear goal in mind, I was able to set out with enthusiasm despite being able to see all the obstacles in my path (like having the... Continue Reading →

# My #GirlDad Tribute

With the recent death of Kobe Bryant and his daughter in a tragic helicopter accident, many have been reflecting on what it means to be a #GirlDad, and thinking about it, I realized that I wanted to pay tribute to my own dad who did a great job of raising his girl in a time... Continue Reading →

# Data structures for deep learning

I recently completed the Udacity Deep Learning Nanodegree (highly worth doing by the way), which focuses on implementing a variety of deep learning architectures using PyTorch. At the outset, it's pretty fundamental to understand the data structures you'll be encountering as inputs to and outputs from your neural network architecture. What I noticed was that... Continue Reading →

# How to – KMeans clustering

Clustering is a type of unsupervised learning. Us humans would think of it as 'categorization' perhaps. For example, if I gave you a bag of red, blue and white balls and asked you to sort them (without telling you how) you would probably naturally gravitate towards sorting them by colour as this would be the... Continue Reading →