My Journey into Machine Learning with AI

I’m alive! Sorry for the lengthy lapse in updates, but things have been so busy. With the release of some of my work as of late, I now have some time to share what I have been working on. As the title suggests, its all around machine learning and artificial intelligence (AI). Despite being hot buzzwords, there are tons of success stories using the technology today. To explain what I have learned, I have written a blog series. My hope is to cover my journey in machine learning with artificial intelligence.

Blog Focus: Machine Learning

Journey into Machine Learning AI
 
First focus is around the technology. As with all new technology it has new terms and new concepts. Several of these are heretical to the status quo, so its important to set a proper level set.  Then we want to discuss where it applies. What problems does it solve? How well do they solve them? How do the new solutions compare to legacy ones?

Solving Problems with Machine Learning

Journey into Machine Learning AI 
Now we have a firm introduction, lets solve some problems. First with the use case of fault storm management. How are storms detected and mitigated? What are the rewards of using ML/AI when applied?
 
My next favorite use case is around fault stream reduction. Fewer faults mean less effort for operations. Can ML/AI help? How well does it work? How hard is it to use?
 
Operational performance management is a touchy subject, but a worthwhile exercise. Why should you monitoring your NOC? How can help operations without being Orwellian about it?
 
Chronic Detection & Mitigation is a common use case for operations. How does operations iron out the wrinkles of their network?  Can operations know when to jump on a chronic to fix them for good. Getting to 99.999% is hard without addressing chronic problems.
 

What is the Future of Machine Learning

Journey into Machine Learning AI
As part of this series, we should address the future of this technology. With ML/AI being so popular, where should this technology be applied? How can it help with service assurance to make an impact.
 
The plan is to wrap up the series with a review of what is currently available in the marketplace. So we are all are aware of what is current versus what is possible.
 
Stay tuned, the plan is to release the blogs weekly. Don’t be afraid to drop comments or questions, as would love to do a AMA or blog on the questions.

Article Map

Journey into Machine Learning AI

About the Author

Serial entrepreneur and operations subject matter expert who likes to help customers and partners achieve solutions that solve critical problems.   Experience in traditional telecom, ITIL enterprise, global manage service providers, and datacenter hosting providers.   Expertise in optical DWDM, MPLS networks, MEF Ethernet, COTS applications, custom applications, SDDC virtualized, and SDN/NFV virtualized infrastructure.  Based out of Dallas, Texas US area and currently working for one of his founded companies – Monolith Software.

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