The Subtleties of Converting a Model from TensorFlow to PyTorch
Advice and techniques to ensure success- 20911Murphy ≡ DeepGuide
Solving Unity Environment with Deep Reinforcement Learning
End to End Project with code of a PyTorch implementation of Deep Reinforcement Learning Agent.- 21772Murphy ≡ DeepGuide
Image Registration for Medical Datasets
From SimpleElastix to Spatial Transformer Networks- 24873Murphy ≡ DeepGuide
Build a Segmentation Model with One Line of Code
Build and train a neural network model for image segmentation in the fastest way- 29220Murphy ≡ DeepGuide
Implementing Vision Transformer (ViT) from Scratch
Understand how Vision Transformer (ViT) works by implementing it from scratch- 25069Murphy ≡ DeepGuide
Clean Code in PyTorch: Best Practices for Readable ML
Five Tips for Writing Clean, Efficient and readable Code in PyTorch- 29623Murphy ≡ DeepGuide
Intro to TorchData: A Walkthrough with Conceptual Captions 3M
Learn how to use TorchData and DataPipes to efficiently stream large datasets like Conceptual Captions 3M.- 20434Murphy ≡ DeepGuide
Introduction to PyTorch: from training loop to prediction
An introduction to PyTorch's training loop and general approach to tackle the library's steeper initial learning curve- 28457Murphy ≡ DeepGuide
Grad-CAM in Pytorch: Use of Forward and Backward Hooks
Using gradients to understand how your model predicts- 22259Murphy ≡ DeepGuide
Implementing Deep Learning Using fastai – Image Classification
Get a head-start in deep learning quickly and easily without wading through all the details- 22212Murphy ≡ DeepGuide
Whisper JAX vs PyTorch: Uncovering the Truth about ASR Performance on GPUs
Deep Dive into Automatic Speech Recognition: Benchmarking Whisper JAX and PyTorch Implementations Across Platforms- 22302Murphy ≡ DeepGuide
Cook your First U-Net in PyTorch
A magic recipe to empower your image segmentation projects- 23329Murphy ≡ DeepGuide
Replace Manual Normalization with Batch Normalization in Vision AI Models
A neat trick to avoid expensive manual pixel normalization for Vision (Image/Video) AI models is to stick a Batch normalization layer as...- 23289Murphy ≡ DeepGuide
Tips and Tricks for Upgrading to PyTorch 2.0
What to look out for when moving to the all-new "Compiled Mode"- 20767Murphy ≡ DeepGuide
Implement interpretable neural models in PyTorch!
Hands-on tutorials to implement interpretable concept-based models with the "PyTorch, Explain!" library.- 26114Murphy ≡ DeepGuide
PyTorch Model Performance Analysis and Optimization
How to Use PyTorch Profiler and TensorBoard to Accelerate Training and Reduce Cost- 27349Murphy ≡ DeepGuide
NT-Xent (Normalized Temperature-Scaled Cross-Entropy) Loss Explained and Implemented in PyTorch
An intuitive explanation of the NT-Xent loss with a step-by-step explanation of the operation and our implementation in PyTorch- 21135Murphy ≡ DeepGuide
Efficient Image Segmentation Using PyTorch: Part 4
A Vision Transformer-based model- 29972Murphy ≡ DeepGuide
Efficient Image Segmentation Using PyTorch: Part 1
Concepts and Ideas- 26067Murphy ≡ DeepGuide
Efficient Image Segmentation Using PyTorch: Part 2
A CNN-based model- 24749Murphy ≡ DeepGuide
We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag