Microsoft Ignite 2019: Developer's Guide to AI

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Microsoft Ignite 2019: Developer's Guide to AI

Author: Microsoft Ignite 2019

Artificial Intelligence (AI) is driving innovative solutions across all industries, but with Machine Learning (ML) applying a paradigm change to how we approach building... Read more

What You Will Learn

  • Azure Cognitive Services
  • Azure Cognitive Search
  • Power BI
  • Azure Notebooks
  • Azure Machine Learning Visual Interface
  • Jupyter, Visual Studio Code
  • Automated ML
  • ML Compute (GPU)
  • Azure DevOps

Pre-requisites

None.

Developer's Guide to AI

Artificial Intelligence (AI) is driving innovative solutions across all industries, but with Machine Learning (ML) applying a paradigm change to how we approach building products we are all exploring how to expand our skillsets. Tailwind Traders is a retail company looking for support on how to benefit from applying AI across their business. In 'Developer's Guide to AI,’ we’ll show how Tailwind Traders has achieved this. There is something for every stage of the AI learning curve; whether you want to consume ML technologies, increase technical knowledge of ML theory, or build your own custom ML models. The model is not the end of the data science story, we conclude with applying DevOps practices to ML projects to build an end-to-end pipeline. This event covers Advanced (level 300) Content and includes the following technologies: Azure Cognitive Services, Azure Cognitive Search, Power BI, Azure Notebooks, Azure Machine Learning Visual Interface, Jupyter, Visual Studio Code, Automated ML, ML Compute (GPU), and Azure DevOps​.

These courses should be watched sequentially.

Making Sense of Your Unstructured Data with AI

by Microsoft Ignite 2019

Feb 12, 2020 / 46m

46m

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Description

Tailwind Traders has a lot of legacy data that they’d like their developers to leverage in their apps – from various sources, both structured and unstructured, and including images, forms, and several others. In this session, learn how the team used Azure Cognitive Search to make sense of this data in a short amount of time and with amazing success. We discuss tons of AI concepts, like the ingest-enrich-explore pattern, search skillsets, cognitive skills, natural language processing, computer vision, and beyond.

Table of contents
  1. Making Sense of Your Unstructured Data with AI

Using Pre-built AI to Solve Business Challenges

by Microsoft Ignite 2019

Feb 12, 2020 / 47m

47m

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Description

As a data-driven company, Tailwind Traders understands the importance of using artificial intelligence to improve business processes and delight customers. Before investing in an AI team, their existing developers were able to demonstrate some quick wins using pre-built AI technologies. In this session, we show how you can use Azure Cognitive Services to extract insights from retail data and go into the neural networks behind computer vision. Learn how it works and how to augment the pre-built AI with your own images for custom image recognition applications.

Table of contents
  1. Using Pre-built AI to Solve Business Challenges

Start Building Machine Learning Models Faster Than You Think

by Microsoft Ignite 2019

Feb 12, 2020 / 40m

40m

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Description

Tailwind Traders uses custom machine learning models to fix their inventory issues – without changing their software development life cycle! How? Azure Machine Learning Visual Interface. In this session, learn the data science process that Tailwind Traders’ uses and get an introduction to Azure Machine Learning Visual Interface. See how to find, import, and prepare data, select a machine learning algorithm, train and test the model, and deploy a complete model to an API. Get the tips, best practices, and resources you and your development team need to continue your machine learning journey, build your first model, and more.

Table of contents
  1. Start Building Machine Learning Models Faster Than You Think

Taking Models to the Next Level with Azure Machine Learning Best Practices

by Microsoft Ignite 2019

Feb 12, 2020 / 47m

47m

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Description

Tailwind Traders’ data science team uses natural language processing (NLP), and recently discovered how to fine tune and build a baseline models with Automated ML. In this session, learn what Automated ML is and why it’s so powerful, then dive into how to improve upon baseline models using examples from the NLP best practices repository. We highlight Azure Machine Learning key features and how you can apply them to your organization, including: low priority compute instances, distributed training with auto scale, hyperparameter optimization, collaboration, logging, and deployment.

Table of contents
  1. Taking Models to the Next Level with Azure Machine Learning Best Practices

Machine Learning Operations: Applying DevOps to Data Science

by Microsoft Ignite 2019

Feb 12, 2020 / 46m

46m

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Description

Many companies have adopted DevOps practices to improve their software delivery, but these same techniques are rarely applied to machine learning projects. Collaboration between developers and data scientists can be limited and deploying models to production in a consistent, trustworthy way is often a pipe dream. In this session, learn how Tailwind Traders applied DevOps practices to their machine learning projects using Azure DevOps and Azure Machine Learning Service. We show automated training, scoring, and storage of versioned models, wrap the models in Docker containers, and deploy them to Azure Container Instances or Azure Kubernetes Service. We even collect continuous feedback on model behavior so we know when to retrain.

Table of contents
  1. Machine Learning Operations: Applying DevOps to Data Science