Review: Mastering Azure Machine Learning

Last week i stumbled upon this book and this weekend there was enough time to walk through it:

 

The book contains 14 chapters on 409 pages - but due to the layout, i think it can fit on 200 pages on a book with "default rendering".
The book is in addition divided in 4 sections: 1 - Azure Machine Learning / 2 - Experimentation and Data Preperation / 3 - Training Machine Learning Models / 4 Optimization and Deployment of Machine Learning Models

Chapter 1 is named "Building an end-to-end machine learning pipeline in Azure". I struggled with this title, but in the first section it is explained: "You can see it as an overview of the book". The subsections cover data exploration, data preparation, choosing the model, optimization and deploying/operating models. The chapter is a teaser with many graphs, examples, stragetgies - a fast end-to-end walk through.

"Choosing a machine learning service in Azure" is the title of the second chapter. Here is everything discussed about ML vs. AI and the Azure services, which provide these techniques (e.g. Data Science Virtual Machine, Azure Batch, Azure Databricks, Azure Functions, Azure IoT Edge, Custom Vision, Azure Machine Learning Designer, Machine Learning Studio,  ...). This chapter contains many screenshots and code snippets - from my point of view to much at this point.

In chapter three (Data experimentation and visualization using Azure) it is shown how to setup your environment via Azure CLI, so that you are able to perform these steps again and again for new projects. In addition it is presented how to run everything on the local machine and track the metrics and artifacts to the Azure workspace. After that visualization is explained including code examples. Pairplots, principal component analysis, quadratic discriminant analysis, stochastic neighbor embedding - Really cool.

Chapter 4 is about "ELT, data preparation and feature extraction". Here are some nice commands with Azure CLI provided: How to batch upload data up to the Azure storage accounts and attaching them to the ML workspace. And how to access this data via python.

Chapter 5 "Azure Machine Learning Pipelines" is about to make the content of chapter 4 reusable. I think nothing to note here - a nice reference for the python code which is needed.

"Advanced feature extraction with NLP" is chapter 6. NLP = natural language processing. Nothing more to say here.

The chaper 7 to 9 are about training machine learning models. I think i will not describe each of them. But here a short summary: It starts with decision trees as explanation and then does a deep dive in how to use LightGBM including the python code. Then the same for convolutional neural networks (CNN): explanation/motivation + coding. This is followed by the description of Azure Hyperdrive: tuning and optimizing the machine learning process. The concept of hyperparameters (e.g. number of neurons in a layer)  is introduced and how to choose them with grid sampling on an elastic cloud infrastructure. And last but not least: it is described how Azure provides "a service to users that automatically preprocesses your data, selects an ML model, and trains and optimizes the model to optimally fit your training data [...]".

Chapter 10 is about using clusters. This is a nice introduction about partitioning data, workloads and synchronizing worker nodes.
"Building a recommendation engine in Azure" is the title of chapter 11. Just some catchwords from the content: non-personalized, contentbased, rating-based, hybrid recommendations. After this chapter you will know, why amazons recommendations are like they are ;-)

In chapter 11 & 12 it is described, how to register, deploy and operate a recommendation engine or machine learning model up to MLOps.

The book closes with chapter 14 "What's next?". Most important point like everywhere: Automation...

Summary: I liked this book very much, because every topic starts with an excellent introduction and there are many code examples, so that you can us this book as reference as well. The basic understanding of the author is best described with the following quote:
"the most important tasks [are]: Data acquisition,  Data cleansing, Data labeling, Selecting an error metric. We don't want to blame anyone, but some machine learning engineers love to simply skip these topics and dive right into the fun parts, namely feature engineering, model selection, parameterization, and tuning." 

That hits the bull's eye.

(The review can be found on amazon as well)

Review: Intent based networking for dummies

I found the book intent-based networking on linkedin posted by juniper:

The book contains 5 chapters on 44 pages.

Chapter one (expressing intent and seeing the basics of IBN) tries to give a motivation for intent based networking. And the story goes like this: "humans are slow, expensive, error prone, and inconsistent. [...] the systems are vulerable to small mistakes that can have enormous costs to business."
In addition we have "inadequate automation", "data overload", and "stale documentation". (At this point i think we are generally doomed and should stop networking at all).
BUT with IBN "you can manage what requires auto- mation, make your system standardized and reliable, and ensure you’re free to move and adjust heading into the future." The promise of IBN is to do a change from node-to-node management to an autonomic system. "The sys tem self-operates, self-adjusts, and self-corrects within the parameters of your expressed technical objectives."
So everthing should work like this: you express your intent - this intent is translated and then orchestration configuration will roll out the changes onto your network.
I think on good phrase for IBN is: "You say what, it says how"

The second chapter is named "Looking at the characteristics of IBN. This chapter does not give any helpful information at all. One nice concept is mentionend here: "Simple Pane of Glass": "t’s an important concept and a valuable benefit of having a single source of truth: You can see your entire network from a single, consistent perspective." But is think this is not possible for networks. Depending on your perspective (ethernet, vlans, ips, mpls, ...) the view is completely different. Just think about hardware ports vs virtual ports...
 

"Detailing the IBN architecture" is the titel of chapter 3. This chapter is with 9 pages the biggest chapter inside the booklet. In this chapter an example is drilled through: The intent "I want a VLAN connecting servers A, B, C, and D." is analyzed and the steps from define, translate, verify, deploy and monitor are shown.
In addition there are some subsection where the reference design, abstractions, inventory are put into relation to each other. This is illustrated with very nice figures. Really a good chapter!
 

In chapter four the book moves forward from fulfillment to assurance. "This chapter shows you why your IBN system (IBNS) requires sophisticated, deep analytics that can detect when a deployed service is drifting out of spec and either automatically make the adjustments to bring it back into compliance or alert you to the problem."
It starts with differentiating uncontrolled changes from controlled changes. This is nothing special to IBN. I think this is useful for any kind of operation in IT.
 

Chapter 5 is as always in this "dummmies" series a recap of the chapters before.


All in all a nice booklet which introduces very well in this new kind of network management system. But if IBN can keep the promises - let's see...
 

Microsoft Teams: How to prevent Teams echo bot from constantly disturbing phone conferences

Some people have found a new hobby: Blowing up Teams meetings.

How do they achieve this?

Very easy. If you are inside a Teams meeting just go to "add members" and type in "Teams echo":

The annoying things about this: 

• This can be done by anyone who was invited and is not limited to your organzation
• On Linux you are not able to invite the Team Echo
• The lobby does not work for Teams Echo - that means he will join you and you have to chance to get rid of that.
• You can not mute Teams Echo
  

Then click on this and you will get the following experience:

 

There is one hint i found:

https://docs.microsoft.com/en-us/answers/questions/284720/can-we-block-or-remove-39teams-echo39-bot-from-ent.html 

Microsoft itself does not really understand the issue:

https://answers.microsoft.com/en-us/msteams/forum/all/teams-echo-entering-into-meetings/3418d131-8619-4785-9ab4-0aed6acbb8c2?auth=1

But this does not work, because you do not find a "Teams echo app" inside https://admin.teams.microsoft.com/policies/manage-apps 

The problem is known:

If you know how to prevent this: Please leave a comment...

Microsoft Ignite: Book of News - March 2021 (Azure et al.)

If you are interested about the new features of Azure, Office 365 and other Microsoft topics, read the Book of New:

https://news.microsoft.com/ignite-march-2021-book-of-news/

 

The table of contents shows the following chapters:

In my opinion chapter 5.4 is one of the most important ones:

https://news.microsoft.com/ignite-march-2021-book-of-news/#a-541-new-security-compliance-and-identity-certifications-and-content-aim-to-close-security-skills-gap

To help address the security skills gap, Microsoft has added four new Security, Compliance and Identity certifications with supporting training and has made several updates to the Microsoft Security Technical Content Library. These certifications and content are intended to help cybersecurity professionals increase their skilling knowledge and keep up with complex cybersecurity threats.

These new certifications with supporting training are tailored to specific roles and needs, regardless of where customers are in their skilling journey:

• The Microsoft Certified: Security, Compliance, and Identity Fundamentals certification will help individuals get familiar with the fundamentals of security, compliance and identity across cloud-based and related Microsoft services.
• The Microsoft Certified: Information Protection Administrator Associate certification focuses on planning and implementing controls that meet organizational compliance needs.
• The Microsoft Certified: Security Operations Analyst Associate certification helps security operational professionals design threat protection and response systems.
• The Microsoft Certified: Identity and Access Administrator Associate certification helps individuals design, implement and operate an organization’s identity and access management systems by using Azure Active Directory (Azure AD).

In addition, the Microsoft Security Technical Content Library contains new technical content and resources.