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Hi, I'm Chris!

I know a thing or two about AI and machine learning. Welcome to MachineCurve.com.

I learn best when teaching others. That's why I decided to start writing about machine learning in May 2019. At the time, deep learning was very hyped, and Transformer architectures were just around the corner.

On this website, you will find all my learnings. They are useful to people wanting to learn more about the fundamentals of machine learning and deep learning. People looking to get started with tools like TensorFlow and PyTorch can find useful information here, too.

Articles about using PyTorch for deep learning

PyTorch, developed by Facebook's AI Research lab (FAIR), is an open-source machine learning framework known for its flexibility and dynamic computation graph. It has gained popularity among researchers and developers for its ease of use, GPU acceleration support, and active community, making it a top choice for various machine learning tasks.

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Greedy layer-wise training of deep networks, a PyTorch example

January 24, 2022

Quick and easy GPU & TPU acceleration for PyTorch with HuggingFace Accelerate

January 7, 2022

How to use Upsample for upsampling with PyTorch

December 28, 2021

Cropping layers with PyTorch

November 10, 2021

How to use TensorBoard with PyTorch

November 10, 2021

How to use L1, L2 and Elastic Net regularization with PyTorch?

July 21, 2021

How to create a neural network for regression with PyTorch

July 20, 2021

How to use PyTorch loss functions

July 19, 2021

Building a simple vanilla GAN with PyTorch

July 17, 2021

Creating DCGAN with PyTorch

July 15, 2021

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