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A Tutorial on Model CI with W&B Automations
Carey Phelps, Thomas CapelleJul 20Articles, Intermediate, MLOps, MNIST, W&B Features, Tables, Domain Agnostic
Next Frame Prediction Using Diffusion: The fastai Approach
Thomas CapelleJan 23Articles, Intermediate, Diffusion, fastai, MNIST, GenAI, Plots, Panels, Tables, Computer Vision
Configuring W&B Projects with Hydra
Adrish DeyFeb 03Beginner, Computer Vision, Classification, Hydra, Tutorial, Panels, Sweeps, CIFAR10, MNIST
Normalization Series: What is Batch Normalization?
Saurav MaheshkarDec 03Intermediate, Domain Agnostic, PyTorch, Tutorial, Conv2D, Plots, Tables, MNIST, Normalization, Chum here, Exemplary
iTAML: An Incremental Task-Agnostic Meta-learning Approach
Joel JosephOct 15Intermediate, Computer Vision, Classification, Research, iTAML, Github, Panels, Plots, Sweeps, CIFAR-100, CIFAR10, MNIST, RC
Meta-Consolidation for Continual Learning (MERLIN)
Shambhavi MishraOct 08Intermediate, Computer Vision, Classification, Research, Plots, CIFAR10, ImageNet, MNIST
The Reality Behind Optimization of Imaginary Variables - II
Darshan DeshpandeOct 05Advanced, Domain Agnostic, Keras, Experiment, Guide, Panels, Plots, Slider, MNIST
Backpropagated Gradient Representations for Anomaly Detection
Shambhavi MishraSep 23Intermediate, Computer Vision, Classification, Research, GradCon, Github, Plots, CIFAR10, MNIST, RC
Using AWS Sagemaker and Weights & Biases Together on Digit Recognition with MNIST
Costa HuangJul 27Beginner, Computer Vision, OCR, PyTorch, SageMaker, Tutorial, Github, Panels, Parameter Importance, Plots, Sweeps, Tables, MNIST
Data Science Experiments Management with Weights & Biases
BroutonLab teamJun 04Beginner, Domain Agnostic, Case Study, W&B Meta, Artifacts, Custom Charts, Panels, Plots, Sweeps, MNIST
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks
Laura R Edmondson, Anil OzdemirApr 21Intermediate, Computer Vision, OCR, Object Detection, Research, SNN, Github, Panels, Parameter Importance, Plots, Sweeps, CIFAR10, MNIST, RC
La-MAML: Look-ahead Meta Learning for Continual Learning
Joel JosephApr 06Intermediate, Computer Vision, Object Detection, Research, Plots, CIFAR-100, ImageNet, MNIST, RC
An Introduction to Adversarial Latent Autoencoders
Ayush Thakur, Sairam SundaresanNov 23Intermediate, Computer Vision, GenAI, Experiment, Research, GAN, Github, Panels, Plots, Slider, MNIST
Object Localization With Keras and Weights & Biases
Ayush ThakurOct 27Intermediate, Computer Vision, Object Detection, Keras, Experiment, Conv2D, Github, Panels, Plots, MNIST
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