Transformers
nlp
transformers
attention
Transformers were introduced in the paper Attention is all you need in 2017 by Vaswani et al, and as the title suggests focusses heavily on a something called attention. This architecture is still very much in use today and is used in text applications applications like ChatGPT, but also in other fields such as vision, audio and other…
N-gram language models
n-gram
nlp
embeddings
generative
In this post, I’ll discuss a very simple language model: n-grams! To keep things simple we will be…
nntrain (4/n): Accelerated optimization
weight decay
momentum
RMSProp
Adam
Resnet
learning rate scheduler
data augmentation
computer vision
In this series, I want to discuss the creation of a small PyTorch based library for training neural networks:
nntrain. It’s based off the excellent part 2 of Practical Deep Learning for Coders by Jeremy Howard, in which from lessons 13 to 18 (roughly)… 
nntrain (3/n): Activations, Initialization and Normalization
convolutions
activations
initialization
batch normalization
computer vision
In this series, I want to discuss the creation of a small PyTorch based library for training neural networks:
nntrain. It’s based off the excellent part 2 of Practical Deep Learning for Coders by Jeremy Howard, in which from lessons 13 to 18 (roughly)… 
nntrain (2/n): Learner
training
momentum
subscribers
learning rate finder
computer vision
In this series, I want to discuss the creation of a small PyTorch based library for training neural networks:
nntrain. It’s based off the excellent part 2 of Practical Deep Learning for Coders by Jeremy Howard, in which from lessons 13 to 18 (roughly)… 
nntrain (1/n): Datasets and Dataloaders
dataloading
training
collation
sampler
In this series, I want to discuss the creation of a small PyTorch based library for training neural networks:
nntrain. It’s based off the excellent part 2 of Practical Deep Learning for Coders by Jeremy Howard, in which from lessons 13 to 18 (roughly)… 
nntrain (0/n): Preliminaries
foundations
PyTorch
nn.Module
In this series, I want to discuss the creation of a small PyTorch based library for training neural networks:
nntrain. It’s based off the excellent part 2 of Practical Deep Learning for Coders by Jeremy Howard, in which from lessons 13 to 18 (roughly)… 
Introduction to Stable Diffusion - Code
generative
stable diffusion
diffusers
computer vision
In the previous blog post, the main components and some intuition behind Stable…
Introduction to Stable Diffusion - Concepts
generative
stable diffusion
diffusers
computer vision
Stable Diffusion, a generative deep learning algorithm developed in 2022, is capable of creating images from prompts. For example, when presented the prompt: A group of people…
No matching items