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.
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.
Architecture is influenced by many factors:
- Data location
- Data complexity
- Data availability
- Data consumption
- Existing engineering process
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.
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