# Perceptron.blog

Machine Learning & Neuroscience

## Category project

###### 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...

###### 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...

## Category tutorial

###### 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...

###### Quantifying the activity of a neuron

#### Back in 1952 Hodgkin and Huxley found that there are three main types of currents describing the dynamics of a neuron: Sodium (N), Potassium (K), and a leak current, which...

###### 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...

###### 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...

###### 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....

###### 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...

###### 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...

## Category machine learning

###### 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...

###### 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...

###### 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....

###### 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...

## Category loss functions

###### 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....

## Category reinforcement learning

###### 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...

## Category sailing

###### 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...

## Category probabilistic machine learning

###### 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...

###### 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...

## Category neuroscience

###### Quantifying the activity of a neuron

#### Back in 1952 Hodgkin and Huxley found that there are three main types of currents describing the dynamics of a neuron: Sodium (N), Potassium (K), and a leak current, which...