Deploying Deep Learning Models

Deploying Deep Learning Models

In this blog post Deploying Deep Learning Models as Fast Secure REST APIs in Production we will walk through how to turn a trained model into a robust web service ready for real users and real traffic. Deploying a model is about more than shipping code. It’s about...
Run PyTorch in .NET with TorchSharp

Run PyTorch in .NET with TorchSharp

In this blog post Practical ways to run PyTorch in .NET with TorchSharp and more we will walk through reliable ways to use PyTorch from .NET, when to choose each approach, and how the pieces work under the hood. At a high level, you have three good options: write and...
Get Started With Tensors With PyTorch

Get Started With Tensors With PyTorch

In this blog post Get Started With Tensors with PyTorch we will walk through how to work with tensors with simple, copy‑paste examples you can use today. Tensors are the workhorse behind modern AI and numerical computing. Think of them as powerful, N‑dimensional...
Loading and Saving PyTorch Weights

Loading and Saving PyTorch Weights

In this blog post Best Practices for Loading and Saving PyTorch Weights in Production we will map out the practical ways to persist and restore your models without surprises. Whether you build models or manage teams shipping them, understanding how PyTorch saves...
Understanding the Softmax Function in AI

Understanding the Softmax Function in AI

The softmax function is a cornerstone of machine learning, especially in tasks involving classification. It transforms raw prediction scores (logits) into probabilities, making them easy to interpret and use for decision-making. This blog post will dive deep into what...