Tag machine learning
Defusing Diffusion Models
How not to get a headache working with diffusion models.
Diffusion models are all the rage these days. They are a new class of generative models, which are capable of generating high-quality images. They have attracted a lot of attention...
Langevin Monte Carlo: Sampling using Langevin Dynamics
How to sample from a distribution using Langevin Dynamics and why it works.
Generative models rely on the ability to sample from a distribution. When the distribution is known the task of sampling from it is straightforward, for example, sampling from a normal...
Building an Automated Detection of Anomalous RFID Behaviour for a Smart Intercom
On Medium
Having to monitor multiple custom-built intercoms can become a tedious process. A daily routine of checking their state and fearfully awaiting for a Slack notification telling you about one crashing...
Tag statistics
Building an Automated Detection of Anomalous RFID Behaviour for a Smart Intercom
On Medium
Having to monitor multiple custom-built intercoms can become a tedious process. A daily routine of checking their state and fearfully awaiting for a Slack notification telling you about one crashing...
Tag react admin
Getting Started: React Admin
On the Teacode blog
At Teacode.io we come across the need to provide administrative technology on a daily basis. However, knowing that admin panels are not the actual money-maker for our clients we had...
Tag gradient descent
What is gradient descent?
Finding minimums of unobvious functions
Gradient descent is probably one of the most widely used algorithm in Machine Learning and Deep Learning. At the same time, it is one of the easiest to understand. In...
Tag loss functions
What is a Loss Function?
How to formulate the right objective.
Any machine learning student will learn about loss functions sooner rather than later. They are a fundamental element of learning and optimisation, therefore understanding is necessary for mastering machine learning....
Tag Q-learning
AI learns to sail upwind
Solving sailing using Q-Learning
The year 2020 was not the greatest for sailors. The pandemic limited the available options for voyages or even to gather a crew. I am a huge sailing enthusiast and...
Tag sailing
AI learns to sail upwind
Solving sailing using Q-Learning
The year 2020 was not the greatest for sailors. The pandemic limited the available options for voyages or even to gather a crew. I am a huge sailing enthusiast and...
Tag linear regression
What is linear regression?
On fitting a line to your data
Linear Regression (LR) is one of the most fundamental algorithms in machine learning. It is the simplest regression model out there it is very often a fitting solution for a...
Tag probabilistic
Defusing Diffusion Models
How not to get a headache working with diffusion models.
Diffusion models are all the rage these days. They are a new class of generative models, which are capable of generating high-quality images. They have attracted a lot of attention...
Langevin Monte Carlo: Sampling using Langevin Dynamics
How to sample from a distribution using Langevin Dynamics and why it works.
Generative models rely on the ability to sample from a distribution. When the distribution is known the task of sampling from it is straightforward, for example, sampling from a normal...
Tag biological modeling
