## How to Implement Logistic Regression with PyTorch

Understand Logistic Regression and sharpen your PyTorch skills To understand better what we’re going to do next, you can read my previous article about logistic regression: So, what’s our plan for implementing Logistic Regression with PyTorch? Let’s first think of the underlying math that we want to use. There are Read more…

## How to Implement Logistic Regression with TensorFlow

…something not as hard as you may think TL; DR If you are here for a quick solution that just works, then here it is in just 5 lines of code: The long way Now, if you’re still with me it means that you don’t want just to copy + Read more…

## How to implement Logistic Regression with NumPy

Sharpen your NumPy skills while learning Logistic Regression What’s our plan for implementing Logistic Regression in NumPy? Let’s first think of the underlying math that we want to use. There are many ways to define a loss function and then find the optimal parameters for it, among them, here we Read more…

## Understanding Logistic Regression

The math of this method explained in detail What is logistic regression? Logistic regression is just adapting linear regression to a special case where you can have only 2 outputs: 0 or 1. And this thing is most commonly applied to classification problems where 0 and 1 represent two different Read more…

## How to implement Linear Regression with PyTorch

Learn PyTorch basics by implementing linear regression Probably, implementing linear regression with PyTorch is an overkill. This library was made for more complicated stuff like neural networks, complex deep learning architectures, etc. Nevertheless, I think that using it for implementing a simpler machine learning method, like linear regression, is a Read more…