Fundamentals of Deep Learning

Deep learning is a subset of machine learning that relies on deep neural networks. It is how computers identify objects in images, translate speech in real-time, generate artwork and music, and perform other tasks that would have been impossible just a few short years ago. Learn what neural networks are, how they work, and how…

Machine Learning for .NET Developers – An Intro to ML.NET

Need to incorporate machine learning (ML) and AI into your next project, but not excited about learning Python? ML.NET is Microsoft’s open-source ML library for .NET developers. With it, you can create sophisticated machine-learning models, and you can use transfer learning to build neural networks that perform image classification and other computer-vision tasks. And you…

Machine Learning for Software Developers

In this webinar, you will get an intro to Machine Learning using scikit-learn. Machine learning (ML) expands the boundaries of what’s possible by letting software do things that can’t be done algorithmically. From fraud detection and sentiment analysis to spam filtering and facial recognition, it touches lives every day. Learn the basics of machine learning…

Building and Deploying Your First Machine Learning Model with Azure ML

Azure Machine Learning service offers an end-to-end platform to build, train, deploy, and manage machine learning models. The service fully supports open-source technologies such as PyTorch, TensorFlow, and scikit-learn and can be used for any kind of machine learning, from classical ml to deep learning, supervised and unsupervised learning. Attend this session to learn how…

Microsoft Custom Vision: Retrain Model in C#

In the previous post, we went over how to use the Custom Vision Training and Prediction SDKs to programmatically predict image URLs and image files. In this post, we’re going to use those same SDKs to show how to programmatically upload more training images to the service and train a new model with those new…

Microsoft Custom Vision: Creating an Image Classification Model

Creating a model to classify images would usually involve creating your own deep learning model from scratch. This includes having a very large and diverse set of training images with a portion of them set aside as a test set, a good convolutional neural network as the model, and a GPU enabled machine to do…

Microsoft Custom Vision: Predict Images with C#

In the previous post, we showed how to train an image classification model using the Microsoft Custom Vision service as well as to perform a quick test on a new image. However, what if you want to integrate this model into one of your applications that is using C#? Whether it’s an app that runs…

Evaluate Your Models with Cross Validation in ML.NET

Let’s say you’ve been working on a machine learning model and your initial evaluation on test data looks good but is that the same kind of performance you’ll get once you deploy your model to take on actual data it hasn’t seen before? This can happen if your model has overfitted to your data. We…

Save and Read Models in ML.NET

Often times you’ll be iterating on your model to try to get it to perform well with new data, so you’ll be training on it for each of those iterations. However, once you feel like you have a model that you believe is good to use, what do you do next? In this post, we’ll…

Machine Learning with C#: An Introduction to ML.NET

When you think of data science and machine learning two programming languages are going to instantly pop into your mind: Python and R. These two languages are great and I love working with them, but coming from a .NET and C# background myself it would be nice to see some love for data science in…