Probability Distributions Part II – Gaussian, Exponential

In part one of this series, I covered two very basic probability distributions - Bernoulli and multinouli. If you want to find out more about those, or if you wish to learn a bit about what are probability distributions, discrete and continuous random variables, go here. In this post, we're covering two slightly bit more … Continue reading Probability Distributions Part II – Gaussian, Exponential

Probability Distributions Part I – Bernoulli, Multinoulli

Probability distributions are used in statistics to describe how likely a random variable is to take on each of it's possible states. Random variables can be discrete and continuous. A discrete random variable has a finite number of possible outcomes, whereas a continuous random variable has an infinite number of possible outcomes. The Bernoulli distribution … Continue reading Probability Distributions Part I – Bernoulli, Multinoulli

Vectors, Matrices, Tensors – What’s The Difference?

Linear algebra is a branch of mathematics which deals with solving a system of linear equations.  It is widely used throughout science and engineering and it is essential to understanding machine learning algorithms. Linear algebra defines three basic data-structures - vectors, matrices and tensors, which are constantly used in machine and deep learning. In this … Continue reading Vectors, Matrices, Tensors – What’s The Difference?

Where Do I Get My Pretrained Networks?

Pretrained networks are very useful. A pretrained network is a deep learning model which has been already trained on some data and the weights of the model have been made publicly available for free use. The famous example of a pretrained network is the VGG series of networks. VGG stands for "Visual Geometry Group", which … Continue reading Where Do I Get My Pretrained Networks?

Tensorflow Style Transfer That Actually Works

A few days ago, I published a blog post on writing a python program which transfers style onto a content image using Keras, which you can find here. The reason why I wrote it using Keras and not Tensorflow, is that I've been trying to write a functioning Tensorflow style transfer program for two weeks … Continue reading Tensorflow Style Transfer That Actually Works

Implementing A Convolutional Neural Network Using Tensorflow

Image recognition is currently my favorite type of machine learning. I say currently because I find  language translation and NLP quite interesting. Convolutional neural networks, at the time of writing this, are the most efficient and accurate method used for image recognition. While you could use a standard fully connected deep neural network with a … Continue reading Implementing A Convolutional Neural Network Using Tensorflow

Rewriting Siraj Raval’s Game of Thrones Word Vectors Using Tensorflow

Siraj Raval's video on how to make word vectors out of five A Song Of Ice And Fire books is a helpful demonstration of word embeddings, but not so helpful as a tutorial because he uses a bunch of smaller libraries which enable you to do the training of the model in just a couple … Continue reading Rewriting Siraj Raval’s Game of Thrones Word Vectors Using Tensorflow

Activation functions explained

I love this kind of featured images. It makes people think that you are so smart and that you've figured out life. They're hilarious. It it makes the topic of the post seem like it's really deep, pun intended. If you've worked with neural networks even a little bit, you've probably come across the term activation function. … Continue reading Activation functions explained