As an Office 365 Developer and organizer of Office 365 developer events in local community, I have got an opportunity to be featured in November 2019 newsletter.
Much awaited .NET Framework 4.8, newed improvements to .NET Framework has been released today.
The .NET Framework 4.8 includes an updated toolset as well as improvements in several areas:
- [Runtime] JIT and NGEN Improvements
- [BCL] Updated ZLib
- [BCL] Reducing FIPS Impact on Cryptography
- [WinForms] Accessibility Enhancements
- [WCF] Service Behavior Enhancements
- [WPF] High DPI Enhancements, UIAutomation Improvements
You can install .NET 4.8 from .NET Download site. Alternatively, use the following direct links:
For .NET 4.8 Download :
Earlier during Microsoft Ignite 2019 conference, Microsoft Learning team has rolled out exams various role based certification exams for Administrators, Developers, Architects and DevOps engineers.
Initially there was a requirement for passing two exams: AZ-100 and AZ-101
As on 20th March, Microsoft has made announcement to simiplify these requirements by introducing a single exam, instead of taking two exams. Here is how it would look like.
What’s included in AZ-103 ?
You can find them detailed out in official exams page here, but I will give a quick list taken from the official page
Manage Azure subscriptions and resources (15-20%)
- Manage Azure subscriptions
- May include but not limited to: Assign administrator permissions; configure cost center quotas and tagging; configure Azure subscription policies at Azure subscription level
- Analyze resource utilization and consumption
- May include but not limited to: Configure diagnostic settings on resources; create baseline for resources; create and rest alerts; analyze alerts across subscription; analyze metrics across subscription; create action groups; monitor for unused resources; monitor spend; report on spend; utilize Log Search query functions; view alerts in Log Analytics
- Manage resource groups
- May include but not limited to: Use Azure policies for resource groups; configure resource locks; configure resource policies; implement and set tagging on resource groups; move resources across resource groups; remove resource groups
- Managed role based access control (RBAC)
- May include but not limited to: Create a custom role, configure access to Azure resources by assigning roles, configure management access to Azure, troubleshoot RBAC, implement RBAC policies, assign RBAC Roles
Implement and manage storage (5-10%)
- Create and configure storage accounts
- May include but not limited to: Configure network access to the storage account; create and configure storage account; generate shared access signature; install and use Azure Storage Explorer; manage access keys; monitor activity log by using Log Analytics; implement Azure storage replication
- Import and export data to Azure
- May include but not limited to: Create export from Azure job; create import into Azure job; Use Azure Data Box; configure and use Azure blob storage; configure Azure content delivery network (CDN) endpoints
- Configure Azure files
- May include but not limited to: Create Azure file share; create Azure File Sync service; create Azure sync group; troubleshoot Azure File Sync
- Implement Azure backup
- May include but not limited to: Configure and review backup reports; perform backup operation; create Recovery Services Vault; create and configure backup policy; perform a restore operation.
Deploy and manage virtual machines (VMs) (20-25%)
- Create and configure a VM for Windows and Linux
- May include but not limited to: Configure high availability; configure monitoring, networking, storage, and virtual machine size; deploy and configure scale sets
- Automate deployment of VMs
- May include but not limited to: Modify Azure Resource Manager (ARM) template; configure location of new VMs; configure VHD template; deploy from template; save a deployment as an ARM template; deploy Windows and Linux VMs
- Manage Azure VM
- May include but not limited to: Add data discs; add network interfaces; automate configuration management by using PowerShell Desired State Configuration (DSC) and VM Agent by using custom script extensions; manage VM sizes; move VMs from one resource group to another; redeploy VMs
- Manage VM backups
- May include but not limited to: Configure VM backup; define backup policies; implement backup policies; perform VM restore; Azure Site Recovery
Configure and manage virtual networks (20-25%)
- Create connectivity between virtual networks
- May include but not limited to: Create and configure VNET peering; create and configure VNET to VNET; verify virtual network connectivity; create virtual network gateway
- Implement and manage virtual networking
- May include but not limited to: Configure private and public IP addresses, network routes, network interface, subnets, and virtual network
- Configure name resolution
- May include but not limited to: Configure Azure DNS; configure custom DNS settings; configure private and public DNS zones
- Create and configure a Network Security Group (NSG)
- May include but not limited to: Create security rules; associate NSG to a subnet or network interface; identify required ports; evaluate effective security rules
- Implement Azure load balancer
- May include but not limited to: Configure internal load balancer, configure load balancing rules, configure public load balancer, troubleshoot load balancing
- Monitor and troubleshoot virtual networking
- May include but not limited to: Monitor on-premises connectivity, use Network resource monitoring, use Network Watcher, troubleshoot external networking, troubleshoot virtual network connectivity
- Integrate on premises network with Azure virtual network
- May include but not limited to: Create and configure Azure VPN Gateway, create and configure site to site VPN, configure Express Route, verify on premises connectivity, troubleshoot on premises connectivity with Azure
Manage identities (15-20%)
- Manage Azure Active Directory (AD)
- May include but not limited to: Add custom domains; Azure AD Join; configure self-service password reset; manage multiple directories;
- Manage Azure AD objects (users, groups, and devices)
- May include but not limited to: Create users and groups; manage user and group properties; manage device settings; perform bulk user updates; manage guest accounts
- Implement and manage hybrid identities
- May include but not limited to: Install Azure AD Connect, including password hash and pass-through synchronization; use Azure AD Connect to configure federation with on-premises Active Directory Domain Services (AD DS); manage Azure AD Connect; manage password sync and password writeback
- Implement multi-factor authentication (MFA)
- May include but not limited to: Configure user accounts for MFA, enable MFA by using bulk update, configure fraud alerts, configure bypass options, configure Trusted IPs, configure verification methods
Now that said. Wishing all the best to all exam aspirants who would want to become an Microsoft Certified: Azure Administrator Associate.
December 24, 2018 Algorithms, Artificial Intelligence(AI), Computer Vision, Emerging Technologies, Image Classification, Image Recognition, Object Based Image Analysis, Object Classification, Object Detection, Object Recognition, Object Tracking, Pixel Based Image Analysis No comments
It is a common question that has been asked in all Artificial Intelligence Conference or Discussion Forums. Based on my knowledge, I thought of answering some of these questions:
1.) Image Classification (also called Image Recognition): is the process of creating a thematic image where each pixel is assigned a number representing a class / tag (this also includes ‘unclassified’. In a persons image the classes can be “complexion”, “gender”, “ethnicity”, “representational names”, etc.
2.) Pattern Recognition (also called Object Recognition): Identifying/recognising the things or objects in an image. This answers the query – what objects or things are depicted in this image? For example, if you are searching for farm lands in an areal image, and other objects such as tractors, sheep’s, cattle’s etc. There are two classifiers you can familiarize for pattern recognition. Pixel based classification and object based classification.
Here is how both classification will look like one vs the other:
3.) Object Detection: is another confusing terminology, Object Recognition was able to recognize – what type of object it is? Now object detection answers the query – where is this specific object? Object detection is based on the point of interest of any given image; for instance electronic devices such as laptop/mobile phone in picture and recognition talked about the specific information about electronic devices, like name, type and other characteristic of particular interest point.
4.) Object Tracking: Done in motion pictures like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. For example: vehicle tracking in a traffic camera system.Or a Realtime object or people tracking like in Object Detection figure.
In October, During Ignite 2018 Conference in Orlando, Microsoft announced the availability of new free interactive and sandbox based learning platform called “Microsoft Learn”, and during these months Microsoft has been adding more and more specific contents for different roles such as Azure Developer, Azure Administrator, Azure Architect etc.
There is a specific learning path for all roles and you can experience different role based contents being aligned in each bucket.
Soon you will be seeing more specific contents for Power BI, Power Apps, Microsoft Flow and Dynamics 365 etc being added in to this platform.
Benefits of Microsoft Learn:
End of Microsoft Virtual Academy(MVA)
Microsoft Virtual Academy has been a free platform for learning about Microsoft technologies and earn completion certificates etc. Since we have the new interactive learning experience available through Microsoft Learn, Microsoft has decided to phase out Microsoft Virtual Academy and we have received an email confirming the same.
Planned complete retirement of MVA by Jan 29’ 2019.
Excerpt from the email received:
To simplify your tech training journey, we are consolidating our learning resources and retiring Microsoft Virtual Academy in phases, beginning on January 31, 2019. Complete site retirement is scheduled for later in 2019. Check your MVA Dashboard frequently for courses you have started that are retiring. To earn your certificates of completion, be sure to finish any courses by January 31, 2019.
Enough said based on my experience I found Microsoft Learn is the new age learning platform providing gamified experience through the learning curve and earning XP points, unlocking achievements gives you a level of satisfaction.
So join Microsoft Learn today.
December 23, 2018 Algorithms, Artificial Intelligence(AI), Azure AI, Cognitive Services, Compuer Vision Service, Computer Vision API, Custom Vision API, Custom Vision Service, Emerging Technologies, Machine Learning(ML) No comments
Custom Vision Service as part of Azure Cognitive Services landscape of pretrained API services, provides you an ability to customize the state-of-the-art Computer Vision models for your specific use case.
Using custom vision service you can upload set of images of your choice and categorize them accordingly using tags/categories and automatically train the image recognition classifiers to learn from these images and come up with image recognition predictions when you supply an input image. Later consume this service as an API in your existing applications.
For example: Here is how an image of Hollywood Actor – Harrison ford being accurately predicted by the custom model through training using a series of pictures of Harrison Ford through different ages and shapes.
I build this sample during Global AI Bootcamp Letterkenny– Hands on Labs, and will take you further through this article. Harrison Ford is my all time favourite actor.
Another example, Harrison Ford was one among 3 in a photo. Here is how the results would look like.
Here is how Harrison Ford’ sons picture is being predicted as Harrison Ford, due to similar facial characteristics. |f we further train this model, we can improve it’s capabilities to come up with accurate predictions.
Now let us see, how it was implemented.
In this article I am going to use a set of Harrison Ford images found on Google Images and then upload them to Custom Vision service like below. For more accuracy, I tried to collect images of Harrison Ford through different stages of his life, so that computer vision model could evolve to predict more accurate results.
Getting Started with Custom Vision:
The Azure Custom Vision API is a cognitive service that lets you build, deploy and improve custom image classifiers. An image classifier is an AI service that sorts images into classes (tags) according to certain characteristics. Unlike the Computer Vision service, Custom Vision allows you to create your own classifications. The Custom Vision service uses a machine learning algorithm to classify images.
Custom Vision functionality can be divided into two features. Image classification assigns a distribution of classifications to each image. Object detection is similar, but it also returns the coordinates in the image where the applied tags can be found.
To get started with our example, first you need to have a Microsoft Account and Register/Login to https://www.customvision.ai
There going to be five steps of activities we are going to do:
1. Setup a Custom Vision Project
Create a new Project by selecting ‘New Project’ button
Specify the naming as the followed:
2. Upload the Images
a.) Prepare Images
I have gathered a set of images you can download it from here, and extract the HF-Demo-Images.zip in to a folder of your choice.
There are two folders in it first folder(harrisonford) contains all reference images for training the model and second folder(hf-quicktest) contains all the quick test images we are going to use for evaluating the model.
b.) Create Tags
Select ‘+’ icon to create a new tag and create the following tags
Enter Tag Name and click on ‘Save’
c.) Upload Images
Now that we created all the tags, lets upload the images and tag them with respective tags.
Click on ‘Add Images’ button and select the images from “harrisonford” folder to upload.
d.) Assign Tags
Now specify the associated tags in My Tags section, selecting from the drop down
Then click on Upload
Have a review of the images uploaded
Now let us train the model by selecting the green train button on top right hand side of the page
This initiates the first automatic training(Iteration 1) based on the tags you assigned and images associated to it.
Once that step is completed let us review the output of the training.
It shows a precision and Recall of 100% indicates our image classification model is trained now to provide Precision of 100% and Recall of 100%.
PS: Recall means out of the tags which should be predicted correctly, what percentage did our model correctly find?
4. Evaluate the Model
Now that our classifier is trained, let us evaluate the accuracy. For that we are going to use the sample images from “hf-quicktest” folder.
b.) Select a local image or select an image URL
Lets try another image
Next let us try to upload an image of Ben Ford (Harrison Ford’s son)
5. Active Learning
Now that we have couple of accurate predictions, Active Learning involves training the model again from the prediction samples we used. This would make the model evolve to provide us more accurate predictions, for example we correcting the model as it identified that Ben Ford also as Harrison Ford based on similar facial features. In real world, he is a different entity other than his father.
Ben Ford is a Chef by profession. So I am going to upload some of his pictures and tag them as Ben Ford. Also couple of images of both father and son together, and then initiate the training again. Hope they would not feel agitated.
Now if you look at training performance, Precision and Recall values came down a bit, we can realize it is because we have two persons being tagged with some common tags etc.
Let us do a Quick Test with the previous image of Ben Ford again. voilà!, we have some accurate prediction.
Similarly, we can repurpose some of the previous prediction images from Predictions tab and add them with right Tags. Then retrain the model again to evolve the model.
Now that you have learned how you can train Custom Vision API with set of images and retrain them again for more accuracy. Once your training is completed and you are happy with the performance, you can integrate the logic in to your existing apps using Custom Vision REST APIs. You can follow the HOL that covers the integration topic here.
Custom Vision Services provides you state-of-the-art Classification and object detection capabilities to customize it for your specific need with quick and easy steps. This help you reduce your time to market and increase ROI (Return of Investment) for your product lines or ideas.
Start learning today using the below reference links.
Disclaimer: All the images referenced in this article are available on the public domain and there is no way any private images are been included in this examples. We respect Harrison Ford and his family privacy, this article is just an attempt to prove the capabilities of Azure Custom Vision Services, no way intended to insult or invade Mr.Harrison Ford’s privacy.I am a big fan of you sir.