Machine Learning & MLOps

ML-image

What is Machine Learning Machine Learning and How Does it Work?

Machine learning (ML) is the he science of training machines to analyze and learn from data the way humans do. It's the process of using mathematical models of data to help a computer learn without direct instruction. Machine learning uses algorithms to identify patterns within data, and uses those patterns used to create a data model to make predictions. With increased data and experience, the results of machine learning are more accurate—much like how humans improve with more practice.

InCycle provides expert consulting for every aspect of machine learning. Whether you are just getting started, seeking a PoC, or an enterprise level implementation, InCycle is ready to help

 

Machine Learning Accelerator

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Machine Learning is Complex - We Demystify It!


Unfortunately, like many things in the world the reality is not as simple as the dream. Long term implementation of a machine learning solution in production is hard. We have many dependencies to solve for and we can't simply build ad-hoc solutions in reaction to every challenge encountered.

Expert Guidance & Implementation

With machine learning, many things must be considered. We have configuration of initial infrastructure, how we collect data, how we verify data, extract features, analyze, and manage machine resources. We also have to consider what infrastructure we use to serve models, how we manage the end-to-end process while still monitoring every stage including model use in production.

At InCycle, we are very purposeful when we build each of these pillars. Contact our team to learn how we can help!

 

 


In a successful MLOps deployment we see a landscape that looks very similar to a DevOps forward organization. People, processes and tools are well aligned, people understand their roles and automation is highly leveraged. At InCycle, we help companies dramatically increase model training and deployment speed by implementing standardization and automation. As an example engagement, our MLOps Accelerator is comprehensive, mature and enterprise-grade solution that enables your team to quickly realize the benefits of ML.

 

Why MLOps?

 

 

Azure Machine Learning


The best machine learning models, and subsequent training, require automation to iterate quickly and ensure speed to deployment. To help companies deliver on the promise of ML and minimize the training cycle, InCycle offers a Machine Learning Enterprise Accelerator. The packaged offering is designed or teams eager to
take advantage of our advanced and proven ML strategy, including automated machine learning pipelines. 

Machine Learning Pipeline Automation

 

 

 

Architecture is influenced by many factors:

  • Data location
  • Data complexity
  • Data availability
  • Data consumption
  • Existing engineering process
  • Environments

Before any solution can be designed, we first have to understand the problem, challenge or opportunity. InCycle's ML strategy sessions are lead by experienced data and cloud architects that are skilled at listening, understanding business goals, and designing solutions to match. Contact us to schedule your strategy session today!

 

 

 

Despite all the whiz-bang technologies (and they are good!), people are still your most valuable asset

At Incycle, we help companies develop and implement machine learning strategies. Going beyond the technical implementation and orchestration, we train teams and provide long lasting coaching and cultural change. In doing so, we enable customers to "cheat time." overcome challenges, and ultimately realize machine learning benefits far faster (and better) then they would on their own. Want to learn more? Sign-up for a ML team briefing.

 

 

Not sure how to get started?
Select best option to match your goals

 

 

Looking to explore next steps? Want to discuss one or more of the above offers? We can help select the best approach for your goals. Contact us or schedule an immediate call.

 

Machine Learning Accelerator

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What our clients say ...

"If it wasn't for the InCycle team, we probably wouldn't be around to talk about it. What we have accomplished is so little time --- is amazing."

Happy Customer

CTO

"We had some ideas of how to solve the problem, but nothing as elegant as you presented."

Happy Customer

DevOps

"We really appreciate your team going the extra mile --- we didn't even have to ask for it!"

Happy Customer

Architect

“Working with InCycle enabled us to quickly prototype a test environment in Azure with almost no upfront effort.  InCycle’s expertise has shown that they fundamentally understand the technology, listen to customer’s needs and requirements and then can quickly implement a precise customized solution.”

Craig Steinfort

Test Manager