03.
Optimize your machine learning models
You’ve built basic machine learning models, but they don’t work or scale as well as you’d like. Meanwhile, you want to do less manual work to feed those models. Scale up the process with TechCelerated’s Machine Learning offering
04.
Efficient, fine-tuned implementation
Your ML models are working, but they don’t operate at scale, take a lot of work to operate, retrain and deploy, and your basic pipelines aren’t yet integrated into existing applications. TechCelerated can get you there with ML Operationalization Assistance.
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01.
Plot your AI roadmap
You have data, but no insights. We can help you discover how relevant business problems can be solved by machine learning. Engage TechCelerated to complete a business case and feasibility analysis.
02.
Prove it, then model it
You have a clear business problem, relevant and clearly defined data, and ML metrics for success. Now it’s time to build your machine learning models. Engage with TechCelerated to build custom neural network architectures to test, deploy and scale.
01
ML planning
Planning
• Define business goals and potential use cases.
• Identify gaps between “data” and “action.”
• Translate business use cases into ML problems and ML solutions.
02
Predictive modelling
POC-to-MVP
• Build ML models to make predictive decisions.
• Design, train and test ML models using cutting-edge model architecture and tools.
• Gain transformative positive effect of models in action.
01
Deploy and integrate
Application
• Integrate model outputs with various business-critical applications.
• Achieve data integration and model inference at scale.
• Operationalize production-ready ML through MLOps.
02
Manage and optimize
Automation
• Ensure ongoing consistency and repeatability of ML solution.
• Track solution performance, monitor alerts, refresh model.
• Feed future model building with solution automation.
See how our machine learning services can work for you
TechCelerated’s data scientists helped Schnucks develop a machine learning model to predict shopper likelihood to buy certain products. The 12-week proof of concept gave the Schnucks team the opportunity to learn the platform and absorb TechCelerated’s analytic approach in a collaborative environment.