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## All content for data scientists and ML engineers

Adam solvers are the hassle free standard for optimizers. Empirically, Adam solvers converge faster and are more robust towards hyper-parameter …

Adam can be understood as updating weights inversely proportional to the scaled L2 norm (squared) of past gradients. AdaMax extends this to the …

AdamW is very similar to Adam . It only differs in the way how the weight decay is implemented. The way how it's implemented in Adam came from the …

In advanced options we currently only have one option available to users. The "Automated tools generate..." toggle allows you to decide if our …

AI assistants

AI assistants are what we call our AI tooling that you can use to automate parts - or all - of your annotation work. The concept behind them is …

AI assistants status overview

Out of the many questions we get from our users, many concerns the status and training of our AI assistant models. We’re the first to admit this has …

While the Adam optimizer, which made use of momentum as well as the RMS prop, was efficient in adjusting the learning rates and finding the optimal …

ASGD

Average Stochastic Gradient Descent, abbreviated as ASGD, averages the weights that are calculated in every iteration.  w_{t+1}=w_t-\eta \nabla …

ATOM segmenter

ATOM is a an AI-powered segmentation tool that can be used both for instance and semantic segmentation. It is available from the start of every …

Attribute Prediction

Attribute Prediction dashboard Widgets GPU Consumption Running time Inference time Hamming Score VS Number of Iterations Loss VS Number of Iterations …

Attribute Prediction

Sample inference script for torchscript exported image-tagger. The following sample code should be run from the export directory: import torch import …