The Global AI Night is a free evening event organized by multiple communities all over the world that are passionate about Artificial Intelligence on the Microsoft Azure.
During this AI Night you will get inspired through sessions and get your hands dirty during the workshops. By the end of the night you will be able to infuse AI into your applications.
Part 1 - Creating applications that can see, hear, speak or understand - using Microsoft Cognitive Services (1 hour) In this workshop you will be introduced to the Microsoft Azure Cognitive Services, a range of offerings you can use to infuse intelligence and machine learning into your applications without needing to build the code from scratch. We will cover pre-trained AI APIs, such as computer vision and text analytics, that are accessed by REST protocol. nEXT we will dive into Custom AI that uses transfer learning - Microsoft Azure Custom Vision. This enables you to provide a small amount of your own data to train an image classification model. Wrapping the workshop up by building our custom trained AI into an application - using Logic Apps, this technology is ideal for building data pipeline processes that work with your machine learning models.
Part 2 - Is that wine good or bad? A beginner tutorial on how to build a binary classification machine learning model with no code using Azure Machine Learning Visual Interface (1 hour) In this workshop you will be introduced to the data science process for building custom machine learning models using Azure Machine Learning Visual Interface. We will cover how to find, import, and prepare data, selecting a machine learning algorithm, training and testing the model, and how to deploy a complete model to an API. Lastly we will discuss some common data science beginner gotchas and provide additional resources to continue your machine learning journey!
Part 1 - Learn how to train high accuracy machine learning models using automated machine learning (1 hour) Intelligent experiences powered by AI can seem like magic to users. Developing them, however, is cumbersome involving a series of sequential and interconnected decisions along the way that are pretty time consuming. What if there was an automated service that identifies the best machine learning pipelines for a given problem/data? Automated machine learning does exactly that! Learn how to quickly and efficiently build high accuracy ml models for classification, regression and forecasting scenarios using code and code-free pathways.
Part 2 - Crash course on building and accelerating deep learning solutions (1 hour) Learn the end to end process of building deep learning solutions from experimentation to deployment. We will start by experimenting locally with different model architectures and hyperparameters using PyTorch. Then, we’ll show you how to use Azure Machine Learning service to train models at massive scale in the cloud and seamlessly deploy them into production.