Azure Cognitive Services and Bot Framework Visio Stencils
As I searched for a stencil set to create an infographic on Azure AI services (Cognitive Services & Bot Framework), I couldn't find anything. So I decided to create this Visio stencil set on my own. If you are interested, please visit https://www.cloudguy.pro/cognitive-services-bot-framework-visio-stencils/ to download the shapes. I would be glad if anyone of you could spread the word in order to see a lot of awesome AI infographics with the official icons in the future :) If you have any questions or improvement suggestions please contact me so that I can include those suggestions in my next versions.
Azure ML Experimentation
Hi - I have created a Machine Learning Expirementation account on Azure, which I now wish to cancel. When I do so, it tells me that I cannot delete the resource until all nested resources are deleted. I have already deleted the storage account, all that is left is the workspace, which does not have an option to delete. Any Suggestions?
Solution for OCR Forms Processing and Entity Extraction
Need to propose a solution that will ingest scanned copies of Forms and extract entities and fields. For e..g extract Invoice Number, Date, Customer Name, Product Names, Raw Material Names etc from a Invoice form. There are many 3rd party companies which offer the ability to digitize your data. I was wondering what will be good Solution Architecture if we were to implement using Azure? Should we consider Azure Computer Vision, Custom Vision, Entity Linking Intelligence Service API, Named Entity Extraction, LUIS, ML, etc? Any suggestions on how we can approach?New automated machine learning capabilities in Azure Machine Learning service
As part of Azure Machine Learning service general availability, we are excited to announce the new automated machine learning (automated ML) capabilities. Automated ML allows you to automate model selection and hyperparameter tuning, reducing the time it takes to build machine learning models from weeks or months to days, freeing up more time for them to focus on business problems. The making of automated ML was driven by our commitment to improve the productivity of data scientists and democratize AI. By simplifying machine learning, automated ML enables domain experts in the businesses to rapidly build and deploy machine learning solutions. Read about it in the Azure blog.Azure IoT Pipelines with Microsoft AzureDevOps Project for CI/CD
Azure IoT Edge – Hub with Azure DevOps Pipeline Configure continuous integration (CI) and continuous delivery (CD) for your IoT Edge application with DevOps Projects. DevOps Projects simplifies the initial configuration of a build and release pipeline in Azure Pipelines. In the following steps you can see how easy it is to build your Continuous integration and continuous deployment to Azure IoT Edge with DevOps Project. Conclusion : When you connect Microsoft Azure IoT Edge – HUB with your Internet of Things Devices and combine it with Microsoft Azure DevOps Team to develop your Azure IoT Pipeline, then you are in fully control of Continuous integration and continuous deployment to Azure IoT Edge. From here you can make your innovations and Intelligent Cloud & Edge with Artificial Intelligence and Machine Learning to your Devices. You will see that this combination will be Awesome for HealthCare, Smart Cities, Smart Buildings, Infrastructure, and the Tech Industry.How to get started with Azure Machine Learning?
This was a question from a university researcher in the Pacific northwest. The good news is that Azure Machine Learning or Azure ML is a powerful native Platform as a Service (PaaS) offering which has been around since 2015. Mark Garcia, a Cloud Solution Architect at Microsoft, put together a FAQ around Azure Machine Learning: What is our definition of Machine Learning? When you think ML many different things fall into this like AI, neural networks, predictive outcomes. Our ML definition is simple: “Experience” = past data + human input. Past data is often huge – the quantity of data is doubling about every 18 months and that’s only increasing from here. Computers can consider far more variables than a human making the same decision. And what do we mean by human input? Human input takes two forms – the input of the user who is either communicating that the output is what they are looking to see or not. In the case that it’s not, the machine can either self-adjust to deliver better results moving forward or the advanced analytic developer or data scientist can make those changes to the model. How does Azure ML work? Here is a flow diagram for Azure ML: Read more on: Where to go to understand what Azure ML provides How to get started with Azure ML Useful hands on labs you can use to see what Azure ML can do Languages supported by Azure ML Azure ML APIs and Azure ML Experiments published for you to leverage Data sources are supported for Azure ML You can fin these and other topics at Mark`s blog post.Visual Intelligence Made Easy
Easily customize your own state-of-the-art computer vision models that fit perfectly with your unique use case. Just bring a few examples of labeled images and let Custom Vision do the hard work. New Cognitive Service Release - Visit for more information : Custom Vision Service
Machine Learning
Hi, I am a Data Developer and I am very interested in understanding and learning Machine Learning (especially Azure ML). I read the pdf suggested "INTRODUCING AZURE MACHINE LEARNING - A GUIDE FOR TECHNICAL PROFESSIONALS" by David Chappell and I would like to know what to read next and how can I make experiments so I can understand better and become a Data Scientist. Or what trainings or tutorials should I follow? I am asking because I'm very interested in this field of technology and I would like to work in it. I have a very logical thinking and a very sharp mind and I really believe that this would be the perfect job for me. I appreciate your help. King regards, Andreea (a data dev who wants to become an awesome data scientist working with ML)
