AutoML which stands for Automated Machine Learning empowers data teams to quickly build and deploy machine learning models. It aims to reduce the time and expertise required to generate a machine learning model by automating the heavy lifting of preprocessing, feature engineering, model creation, tuning and evaluation. When it comes to machine learning in Microsoft Azure, there are two main options for running your AutoML: (1) Azure Machine Learning Service and (2) Azure Databricks. This session will aim to introduce how to develop ML models using AutoML on both platforms, as well as the features of each and why you would choose one over the other.
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In this talk, we will be leveraging Azure computer vision. The Azure Computer Vision is part of Azure Cognitive Services that provides pre-built, advanced algorithms that process and analyse images. If you want to get started with computer vision but do not know where to start, then this talk will give you a good starting point to jumpstart your computer vision journey. You will leave this talk with an understanding of how to build and deploy your own computer vision models using Azure computer vision.
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Going from an machine learning model trained on your laptop in a notebook called “trainmodelV1Final_FINAL (1).ipynb” to a system ready to deploy is difficult. However, MLOps (a set of principles to prepare your model for prime time) is here to help! This talk is an introduction to all the elements you need to get your code production-ready - CI/CD, dev/UAT/prod, pipelines, and more! We'll walk through system diagrams, with a focus on Azure, but the takeaways will all be platform agnostic. Make sure your model deployment isn’t an ML-Flop!
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We will go through a brief introduction to what Machine Learning is and some of its applications. we will then explore why AutoML should be used by all; as a great starting point for anyone new to Machine Learning, as well as a time saving tool for those more experienced. Finally, we will expose a model as an endpoint and understand how we can use it. Specifically in this case how to use it in excel via VBA. Technologies I will demonstrate are: - Azure Machine Learning Studio - VS code (with Azure Machine Learning Studio extension) - Python - VBA
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Creating a new episode of Buffy the Vampire slayer with Azure Machine Learning
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SQLBits' has brought members of the Azure Synapse Program Group to Wales to ask YOUR questions. Bring your questions for: Dedicated SQL Pools, Serverless SQL Pools, Spark Pools, Pipelines, Kusto and everything else Synapse related.
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In this session, you will get to learn how to enrich your data in spark tables with models created using Automated ML in Azure Synapse Analytics. We will be looking at a demo where we will create regression and classification models using Automated ML and how to use these models for prediction in Azure Synapse Analytics.
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The Key takeaway is that attendees will get ideas about the skills and knowledge required to recognize an opportunity for a machine learning application and seize it. Also attendee gets to know well about Azure Machine Leaning.
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In this session, we will cut through the marketing buzzwords to share experiences, tips, and tricks on how to be successful with Data Science and Analytics in the real world. Tune in to hear the team share real-world experience and get takeaways from industry insiders on real projects with impact. We will also discuss the ethics and fairness of Data Science and Analytics projects and how we can be more inclusive from a technology, people, and process standpoint.
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Reality Check on Microsofts Enterprise Scale Analytics Framework
In this session, we’ll go deep into the internal behavior of SQL Server CPU, including the internal and external memory pressure, worker thread management, and how to troubleshoot CPU problems.
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Curious what Azure Synapse Analytics brings to the table? Bring your scuba gear, as we take a dive and explore everything it has to offer!
Azure Synapse Analytics combines the power of Data Lakes with Data Warehouses, empowering the organizations to build Big Data, Advanced Analytics and Business Intelligence in one single platform.
AI and data is at the center of the digital feedback loops. We have invested in a comprehensive portfolio of AI tools, infrastructure and services. Come to this session to get an update of Azure AI with demos.
Understand how to create, train and operationalize your data science projects in Azure Machine Learning.
Azure Synapse Analytics combines the power of Data Lakes with Data Warehouses, empowering the organizations to build Big Data, Advanced Analytics and Business Intelligence in one single platform.
Microsoft provides a cloud hosted Jupyter Notebook solution with Azure Notebooks, which offer minimal overhead and opportunities for collaboration.
In this session, we will discuss the basics of IA and how we can apply it in our business using the Azure Machine Learning Services
In this session we’ll look at what ML tools are available in the Power BI and Azure worlds, and how you go about using these in your Power BI reports
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
Are you looking to take your career to the next step? Microsoft Certifications help validate knowledge and ability required to perform current and future industry job-roles in a modern digital business. Our certification
Using custom machine learning models to fix inventory issues without changing a development life cycle. In this session, you’ll learn about the data science process and get an intro to Azure ML designer.
Learn how Tailwind Traders data science team uses Azure Machine Learning features and services to create bespoke open source NLP models and optimise them. Includes Automated ML, Azure ML SDK and Hyperparameter tuning
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