There are 2 repositories under weights-and-biases topic.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
๐ ๐ง๐ต๐ฒ ๐๐๐น๐น ๐ฆ๐๐ฎ๐ฐ๐ธ ๐ณ-๐ฆ๐๐ฒ๐ฝ๐ ๐ ๐๐ข๐ฝ๐ ๐๐ฟ๐ฎ๐บ๐ฒ๐๐ผ๐ฟ๐ธ | ๐๐ฒ๐ฎ๐ฟ๐ป ๐ ๐๐ & ๐ ๐๐ข๐ฝ๐ for free by designing, building and deploying an end-to-end ML batch system ~ ๐ด๐ฐ๐ถ๐ณ๐ค๐ฆ ๐ค๐ฐ๐ฅ๐ฆ + 2.5 ๐ฉ๐ฐ๐ถ๐ณ๐ด ๐ฐ๐ง ๐ณ๐ฆ๐ข๐ฅ๐ช๐ฏ๐จ & ๐ท๐ช๐ฅ๐ฆ๐ฐ ๐ฎ๐ข๐ต๐ฆ๐ณ๐ช๐ข๐ญ๐ด
Train a state-of-the-art yolov3 object detector from scratch!
Generic template to bootstrap your PyTorch project.
A clean and structured implementation of Transformer with wandb and pytorch-lightning
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
:dart: Deep Learning Framework for Image Classification & Regression in Pytorch for Fast Experiments
This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.
Tiny ResNet inspired FPN network (<2M params) for Rotated Object Detection using 5-parameter Modulated Rotation Loss
Example codes in the medium post titled "Optuna meets Weights and Biases."
:detective::robot: Monitoring a PyTorch Lightning CNN with Weights & Biases
Python framework for artificial text detection: NLP approaches to compare natural text against generated by neural networks.
Order execution in the financial markets using Deep Reinforcement Learning.
A template repository to quickly get started on a new Machine Learning project.
Training a racecar with W&B!
MLOps Implementing "Brain Computer Interface" on Kubernetes
PyTorch Lightning Implementation of Diffusion, GAN, VAE, Flow models
Solution to the SETI Breakthrough Listen Competition hosted on Kaggle
Deep learning based color transfer between images.
Using GPT-3 to help me get more ๐ on medium.com
Predicting Turbine Energy Yield (TEY) using ambient variables as features.
Recommendation Engine powered by Matrix Factorization.
Machine learning and AI projects require managing diverse data sources, vast data volumes, model and parameter development, and conducting numerous test and evaluation experiments. Overseeing and tracking these aspects of a program can quickly become an overwhelming task.
Pipeline built on flyte for training Iris dataset using Pytorch and Weights and Biases
Experiment on rotation equivariance using Group Convolution U-Nets applied to segmentation of butterfly images
Monitor SLURM jobs using Weights and Biases (wandb) ๐
medium blog posts code
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning (ICML 2022)
Automating machine learning model comparisons using Weights & Biases based on GitHub issues, enabling collaboration and communication.
A dynamically adjustable scoring calculator with a lighthouse style data visualization. Get a score between 0 to 100 from data, with dynamically adjustable target value, a from -5 to +5 adjustable bias , and a self adjusting weighting system.
The notebook here consists of the concept of "Moore Penrose PseudoInverse" which approximates the inverse of a matrix and we use it to find the weight vectors in any given linear regression problem.
This repository contains the experiments to show certain capabilities of Weights and Biases.
Templates for AI projects.