T-Rex hosted an Amazon Web Services (AWS) Partner Network (APN) Immersion Day, enabling its employees to attend a half-day workshop on Machine Learning (ML) and Artificial Intelligence (AI). According to a recent prediction from IDC, by 2026, 75% of all enterprise software will include some aspect of machine/deep learning.
T-Rex’s APN Immersion Day contained five hands-on labs on AWS ML services like Amazon SageMaker, Amazon Deep Learning AMIs, and Amazon SageMaker MLOps.
T-Rex utilizes AWS ML services in areas such as computer vision, language recommendations, and forecasting services, to better serve its customers. Xiaolin Li, Director of Data Engineering and Analytics said “AI/ML services are being used with our current customers and are a key solution in T-Rex offerings. The APN session highlights some exciting AI/ML features such as predictive analytics, computer vision, and forecasting services that we can utilize to reduce cost and make data available for our customers.” Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy ML models quickly. Amazon SageMaker removes the heavy lifting from each step of the ML process to make it easier to develop high quality models.
T-Rex employees learned hands-on how ML and AI can be leveraged in the cloud:
- Terminology
- Services Available
- Use Cases
To get started on your ML journey today, follow these 4 steps below:
- Prepare
- Gather data from various data sources
- Profile data to identify data well fit for modeling
- Assess data for usefulness in the modeling
- Generate a feature data set upon which insights are generated
- Experiment
- Identify possible targets for the models
- Assess the outcomes of those targets against the intended objectives
- Test the ability to meet these targets through various analyses
- Align the modeling plan to the best fit targets and approach
- Model
- Identify possible modeling methods to meet the target needs
- Assess the outcomes of those models against the intended objectives
- Test the ability to meet those targets through the various modeling techniques
- Align the approach to the best fit modeling outputs
- Deploy
- Identify possible integration methods to meet the target needs
- Assess the outcomes of those integration methods against the intended objectives
- Test the ability to meet those targets through the various integration techniques
- Align the approach to the best fit integration approaches
In addition to knowledge gained from this workshop, T-Rex Centers of Excellence (COEs) now have the responsibility to help socialize AI/ML throughout T-Rex and with our clients. As subject matter experts, T-Rex COEs will help get the word out about the benefits of ML/AI by leveraging AWS ML services.
Philip M. Gollucci, Director of Solutions Architecture in the Centers of Excellence, said “A great intro and refresher making AI/ML accessible to the masses regardless of prior experience!”
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